IBM Cognos Framework Manager: Design Metadata Models (V10.1) · IBM Cognos Framework Manager:...

B5152G www.globalknowledge.es [email protected] (34) 91 425 06 60

IBM Cognos Framework Manager: Design Metadata Model s (V10.1)

Duración: 5 Días Código del Curso: B5152G

Temario:

IBM Cognos Education is now pleased to offer you our courses in an exciting new learning format, Instructor-led Online (ILO). Students areoffered a similar experience to live classroom training, with the convenience of having it delivered directly to their desktop.IBM Cognos Framework Manager: Design Metadata Models (V10.1) is a five-day, instructor-led course that provides participants withintroductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis resultsusing Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing ofmetadata to the Web, enabling end users to easily author reports and analyze data.

Dirigido a:

This course is for developers who design metadata models for use in IBM Cognos.

Objetivos:

Please refer to course overview for description information.

Prerequisitos:

Required:

Knowledge of common industry standard data structures anddesignExperience with SQLExperience gathering requirements and analyzing data

Recommended:

IBM Cognos Report Studio: Author Professional ReportsFundamentals (V10.1) or CBT equivalent


Contenido:

line line lineDiscuss IBM Cognos and Performance Describe IBM Cognos components Describe IBM Cognos componentsManagement Describe IBM Cognos architecture at a Describe IBM Cognos architecture at aExamine the characteristics of operational high level high leveldatabases and databases designed for Define IBM Cognos groups and roles Define IBM Cognos groups and rolesreporting Explain how to extend IBM Cognos Explain how to extend IBM CognosExamine key modeling recommendations Identify Common Data Structures Identify Common Data StructuresExamine the IBM Cognos BI and Framework Examine relationships and cardinality Examine relationships and cardinalityManager workflow processes Identify different data traps Identify different data trapsVerify relationships and query item Examine OLAP data sources Examine OLAP data sourcesproperties Gather Requirements Gather RequirementsDescribe multi-fact queries and when full Define reporting requirements Define reporting requirementsouter joins are appropriate Explore data sources to identify data Explore data sources to identify dataIdentify the advantages of modeling access strategies access strategiesmetadata as a star schema Create a Baseline Project Create a Baseline ProjectCreate virtual facts to simplify writing queries Define a project and its structure Define a project and its structureUse calculations to create Describe the Framework Manager Describe the Framework Managercommonly-needed query items for authors environment environmentMake time-based queries simple to author Create a baseline project Create a baseline projectby implementing a time dimension Enhance the model with additional Enhance the model with additionalUse determinants to specify multiple levels metadata metadataof granularity and prevent double-counting Prepare Reusable Metadata Prepare Reusable MetadataIdentify the dimensions associated with a Ensure efficient filters by configuring Ensure efficient filters by configuringfact table prompt properties prompt propertiesIdentify key differences and Model for Predictable Results: Identify Model for Predictable Results: Identifyrecommendations for using data source, Reporting Issues Reporting Issuesmodel, and stored procedure query subjects Describe how IBM Cognos BI uses Describe how IBM Cognos BI usesExamine the IBM Cognos BI security cardinality cardinalityenvironment Identify reporting traps Identify reporting trapsApply dimensional information to relational Use tools to analyze the model Use tools to analyze the modelMetadata to enable OLAP-style queries Model for Predictable Results: Virtual Model for Predictable Results: Virtual StarDescribe model types and data entities Star Schemas SchemasIdentify conformed values between data Model in layers Model in layerssources Create aliases to avoid ambiguous joins Create aliases to avoid ambiguous joinsGovernors that affect SQL generation Merge query subjects to create as view Merge query subjects to create as viewIdentify session and model parameters behavior behaviorPerform basic maintenance and Model for Predictable Results: Model for Predictable Results: Consolidatemanagement on a model Consolidate Metadata MetadataIdentify and implement techniques to Create virtual dimensions to resolve Create virtual dimensions to resolveoptimize and tune your Framework Manager fact-to-fact joins fact-to-fact joinsmodels Create a consolidated modeling layer for Create a consolidated modeling layer forImplement repository control presentation purposes presentation purposesConnect to an OLAP data source (cube) in a Consolidate snowflake dimensions with Consolidate snowflake dimensions withFramework Manager project model query subjects model query subjectsSpecify package languages and function Simplify facts by hiding unnecessary Simplify facts by hiding unnecessary codessets codes Calculations and Filters

Calculations and Filters Use static filters to reduce the dataUse static filters to reduce the data returned

line returned Use macros and parameters inDescribe IBM Cognos components Use macros and parameters in calculations and filters to dynamicallyDescribe IBM Cognos architecture at a high calculations and filters to dynamically control the data returnedlevel control the data returned Implement a Time DimensionDefine IBM Cognos groups and roles Implement a Time Dimension Resolve confusion caused by multipleExplain how to extend IBM Cognos Resolve confusion caused by multiple relationships between a time dimensionIdentify Common Data Structures relationships between a time dimension and another tableExamine relationships and cardinality and another table Specify DeterminantsIdentify different data traps Specify Determinants Create the Presentation ViewExamine OLAP data sources Create the Presentation View Identify conformed vs. non-conformedGather Requirements Identify conformed vs. non-conformed dimensionsDefine reporting requirements dimensions Create star schema groupings to provideExplore data sources to identify data access Create star schema groupings to provide authors with logical groupings of querystrategies authors with logical groupings of query subjectsCreate a Baseline Project subjects Work with Different Query Subject Types


Define a project and its structure Work with Different Query Subject Types Identify the effects on generated SQLDescribe the Framework Manager Identify the effects on generated SQL when modifying query subjects, SQLenvironment when modifying query subjects, SQL settings and relationshipsCreate a baseline project settings and relationships Set Security in Framework ManagerEnhance the model with additional metadata Set Security in Framework Manager Restrict access to packagesPrepare Reusable Metadata Restrict access to packages Create and apply security filtersEnsure efficient filters by configuring prompt Create and apply security filters Restrict access to objects in the modelproperties Restrict access to objects in the model Create Analysis ObjectsModel for Predictable Results: Identify Create Analysis Objects Sort members for presentation andReporting Issues Sort members for presentation and predictabilityDescribe how IBM Cognos BI uses predictability Manage MUNs in Framework Managercardinality Manage MUNs in Framework Manager Define members and member uniqueIdentify reporting traps Define members and member unique namesUse tools to analyze the model names Identify changes that impact a MUNModel for Predictable Results: Virtual Star Identify changes that impact a MUN Model for Drill Through in FrameworkSchemas Model for Drill Through in Framework ManagerModel in layers Manager Define a report drill throughCreate aliases to avoid ambiguous joins Define a report drill through Define a package-based drill throughMerge query subjects to create as view Define a package-based drill through Identify drill-through valuesbehavior Identify drill-through values Advanced Generated SQL Concepts andModel for Predictable Results: Consolidate Advanced Generated SQL Concepts and Complex QueriesMetadata Complex Queries Stitch query SQLCreate virtual dimensions to resolve Stitch query SQL Conformed and non-conformedfact-to-fact joins Conformed and non-conformed dimensions in generated SQLCreate a consolidated modeling layer for dimensions in generated SQL Multi-fact/multi-grain stitch query SQLpresentation purposes Multi-fact/multi-grain stitch query SQL Variances in Report Studio generated SQLConsolidate snowflake dimensions with Variances in Report Studio generated Dimensionally modeled relational SQLmodel query subjects SQL generationSimplify facts by hiding unnecessary codes Dimensionally modeled relational SQL Cross join SQLCalculations and Filters generation Various results sets for multi-fact queriesUse static filters to reduce the data returned Cross join SQL Use Advanced ParameterizationUse macros and parameters in calculations Various results sets for multi-fact queries Techniques in Framework Mangerand filters to dynamically control the data Use Advanced Parameterization Leverage session, model, and customreturned Techniques in Framework Manger parametersImplement a Time Dimension Leverage session, model, and custom Create prompt macrosResolve confusion caused by multiple parameters Leverage macro functions associated withrelationships between a time dimension and Create prompt macros securityanother table Leverage macro functions associated Model Maintenance and ExtensibilitySpecify Determinants with security Remap metadata to another sourceCreate the Presentation View Model Maintenance and Extensibility Import and link a second data sourceIdentify conformed vs. non-conformed Remap metadata to another source Run scripts to automate or update a modeldimensions Import and link a second data source View lineageCreate star schema groupings to provide Run scripts to automate or update a Create a model reportauthors with logical groupings of query model Optimize and Tune Framework Managersubjects View lineage ModelsWork with Different Query Subject Types Create a model report Work in a Multi-Modeler EnvironmentIdentify the effects on generated SQL when Optimize and Tune Framework Manager Segment and link a projectmodifying query subjects, SQL settings and Models Branch a project and merge resultsrelationships Work in a Multi-Modeler Environment Manage OLAP Data SourcesSet Security in Framework Manager Segment and link a project Publish an OLAP modelRestrict access to packages Branch a project and merge results Publish a model with multiple OLAP dataCreate and apply security filters Manage OLAP Data Sources sourcesRestrict access to objects in the model Publish an OLAP model Publish a model with an OLAP data sourceCreate Analysis Objects Publish a model with multiple OLAP data and a relational data sourceSort members for presentation and sources Manage Framework Manager Packagespredictability Publish a model with an OLAP data Control model versioningManage MUNs in Framework Manager source and a relational data source Nest packagesDefine members and member unique names Manage Framework Manager PackagesIdentify changes that impact a MUN Control model versioningModel for Drill Through in Framework Nest packages lineManager Discuss IBM Cognos and PerformanceDefine a report drill through ManagementDefine a package-based drill through line Examine the characteristics of operationalIdentify drill-through values Describe IBM Cognos components databases and databases designed forAdvanced Generated SQL Concepts and Describe IBM Cognos architecture at a reportingComplex Queries high level Examine key modeling recommendations


Stitch query SQL Define IBM Cognos groups and roles Examine the IBM Cognos BI andConformed and non-conformed dimensions Explain how to extend IBM Cognos Framework Manager workflow processesin generated SQL Identify Common Data Structures Verify relationships and query itemMulti-fact/multi-grain stitch query SQL Examine relationships and cardinality propertiesVariances in Report Studio generated SQL Identify different data traps Describe multi-fact queries and when fullDimensionally modeled relational SQL Examine OLAP data sources outer joins are appropriategeneration Gather Requirements Identify the advantages of modelingCross join SQL Define reporting requirements metadata as a star schemaVarious results sets for multi-fact queries Explore data sources to identify data Create virtual facts to simplify writingUse Advanced Parameterization Techniques access strategies queriesin Framework Manger Create a Baseline Project Use calculations to createLeverage session, model, and custom Define a project and its structure commonly-needed query items for authorsparameters Describe the Framework Manager Make time-based queries simple to authorCreate prompt macros environment by implementing a time dimensionLeverage macro functions associated with Create a baseline project Use determinants to specify multiple levelssecurity Enhance the model with additional of granularity and prevent double-countingModel Maintenance and Extensibility metadata Identify the dimensions associated with aRemap metadata to another source Prepare Reusable Metadata fact tableImport and link a second data source Ensure efficient filters by configuring Identify key differences andRun scripts to automate or update a model prompt properties recommendations for using data source,View lineage Model for Predictable Results: Identify model, and stored procedure queryCreate a model report Reporting Issues subjectsOptimize and Tune Framework Manager Describe how IBM Cognos BI uses Examine the IBM Cognos BI securityModels cardinality environmentWork in a Multi-Modeler Environment Identify reporting traps Apply dimensional information to relationalSegment and link a project Use tools to analyze the model Metadata to enable OLAP-style queriesBranch a project and merge results Model for Predictable Results: Virtual Describe model types and data entitiesManage OLAP Data Sources Star Schemas Identify conformed values between dataPublish an OLAP model Model in layers sourcesPublish a model with multiple OLAP data Create aliases to avoid ambiguous joins Governors that affect SQL generationsources Merge query subjects to create as view Identify session and model parametersPublish a model with an OLAP data source behavior Perform basic maintenance andand a relational data source Model for Predictable Results: management on a modelManage Framework Manager Packages Consolidate Metadata Identify and implement techniques toControl model versioning Create virtual dimensions to resolve optimize and tune your FrameworkNest packages fact-to-fact joins Manager models

Create a consolidated modeling layer for Implement repository controlpresentation purposes Connect to an OLAP data source (cube) in

line Consolidate snowflake dimensions with a Framework Manager projectDescribe IBM Cognos components model query subjects Specify package languages and functionDescribe IBM Cognos architecture at a high Simplify facts by hiding unnecessary setslevel codesDefine IBM Cognos groups and roles Calculations and FiltersExplain how to extend IBM Cognos Use static filters to reduce the data lineIdentify Common Data Structures returned Describe IBM Cognos componentsExamine relationships and cardinality Use macros and parameters in Describe IBM Cognos architecture at aIdentify different data traps calculations and filters to dynamically high levelExamine OLAP data sources control the data returned Define IBM Cognos groups and rolesGather Requirements Implement a Time Dimension Explain how to extend IBM CognosDefine reporting requirements Resolve confusion caused by multiple Identify Common Data StructuresExplore data sources to identify data access relationships between a time dimension Examine relationships and cardinalitystrategies and another table Identify different data trapsCreate a Baseline Project Specify Determinants Examine OLAP data sourcesDefine a project and its structure Create the Presentation View Gather RequirementsDescribe the Framework Manager Identify conformed vs. non-conformed Define reporting requirementsenvironment dimensions Explore data sources to identify dataCreate a baseline project Create star schema groupings to provide access strategiesEnhance the model with additional metadata authors with logical groupings of query Create a Baseline ProjectPrepare Reusable Metadata subjects Define a project and its structureEnsure efficient filters by configuring prompt Work with Different Query Subject Types Describe the Framework Managerproperties Identify the effects on generated SQL environmentModel for Predictable Results: Identify when modifying query subjects, SQL Create a baseline projectReporting Issues settings and relationships Enhance the model with additionalDescribe how IBM Cognos BI uses Set Security in Framework Manager metadatacardinality Restrict access to packages Prepare Reusable MetadataIdentify reporting traps Create and apply security filters Ensure efficient filters by configuring


Use tools to analyze the model Restrict access to objects in the model prompt propertiesModel for Predictable Results: Virtual Star Create Analysis Objects Model for Predictable Results: IdentifySchemas Sort members for presentation and Reporting IssuesModel in layers predictability Describe how IBM Cognos BI usesCreate aliases to avoid ambiguous joins Manage MUNs in Framework Manager cardinalityMerge query subjects to create as view Define members and member unique Identify reporting trapsbehavior names Use tools to analyze the modelModel for Predictable Results: Consolidate Identify changes that impact a MUN Model for Predictable Results: Virtual StarMetadata Model for Drill Through in Framework SchemasCreate virtual dimensions to resolve Manager Model in layersfact-to-fact joins Define a report drill through Create aliases to avoid ambiguous joinsCreate a consolidated modeling layer for Define a package-based drill through Merge query subjects to create as viewpresentation purposes Identify drill-through values behaviorConsolidate snowflake dimensions with Advanced Generated SQL Concepts and Model for Predictable Results: Consolidatemodel query subjects Complex Queries MetadataSimplify facts by hiding unnecessary codes Stitch query SQL Create virtual dimensions to resolveCalculations and Filters Conformed and non-conformed fact-to-fact joinsUse static filters to reduce the data returned dimensions in generated SQL Create a consolidated modeling layer forUse macros and parameters in calculations Multi-fact/multi-grain stitch query SQL presentation purposesand filters to dynamically control the data Variances in Report Studio generated Consolidate snowflake dimensions withreturned SQL model query subjectsImplement a Time Dimension Dimensionally modeled relational SQL Simplify facts by hiding unnecessary codesResolve confusion caused by multiple generation Calculations and Filtersrelationships between a time dimension and Cross join SQL Use static filters to reduce the dataanother table Various results sets for multi-fact queries returnedSpecify Determinants Use Advanced Parameterization Use macros and parameters inCreate the Presentation View Techniques in Framework Manger calculations and filters to dynamicallyIdentify conformed vs. non-conformed Leverage session, model, and custom control the data returneddimensions parameters Implement a Time DimensionCreate star schema groupings to provide Create prompt macros Resolve confusion caused by multipleauthors with logical groupings of query Leverage macro functions associated relationships between a time dimensionsubjects with security and another tableWork with Different Query Subject Types Model Maintenance and Extensibility Specify DeterminantsIdentify the effects on generated SQL when Remap metadata to another source Create the Presentation Viewmodifying query subjects, SQL settings and Import and link a second data source Identify conformed vs. non-conformedrelationships Run scripts to automate or update a dimensionsSet Security in Framework Manager model Create star schema groupings to provideRestrict access to packages View lineage authors with logical groupings of queryCreate and apply security filters Create a model report subjectsRestrict access to objects in the model Optimize and Tune Framework Manager Work with Different Query Subject TypesCreate Analysis Objects Models Identify the effects on generated SQLSort members for presentation and Work in a Multi-Modeler Environment when modifying query subjects, SQLpredictability Segment and link a project settings and relationshipsManage MUNs in Framework Manager Branch a project and merge results Set Security in Framework ManagerDefine members and member unique names Manage OLAP Data Sources Restrict access to packagesIdentify changes that impact a MUN Publish an OLAP model Create and apply security filtersModel for Drill Through in Framework Publish a model with multiple OLAP data Restrict access to objects in the modelManager sources Create Analysis ObjectsDefine a report drill through Publish a model with an OLAP data Sort members for presentation andDefine a package-based drill through source and a relational data source predictabilityIdentify drill-through values Manage Framework Manager Packages Manage MUNs in Framework ManagerAdvanced Generated SQL Concepts and Control model versioning Define members and member uniqueComplex Queries Nest packages namesStitch query SQL Identify changes that impact a MUNConformed and non-conformed dimensions Model for Drill Through in Frameworkin generated SQL line ManagerMulti-fact/multi-grain stitch query SQL Describe IBM Cognos components Define a report drill throughVariances in Report Studio generated SQL Describe IBM Cognos architecture at a Define a package-based drill throughDimensionally modeled relational SQL high level Identify drill-through valuesgeneration Define IBM Cognos groups and roles Advanced Generated SQL Concepts andCross join SQL Explain how to extend IBM Cognos Complex QueriesVarious results sets for multi-fact queries Identify Common Data Structures Stitch query SQLUse Advanced Parameterization Techniques Examine relationships and cardinality Conformed and non-conformedin Framework Manger Identify different data traps dimensions in generated SQLLeverage session, model, and custom Examine OLAP data sources Multi-fact/multi-grain stitch query SQLparameters Gather Requirements Variances in Report Studio generated SQL


Create prompt macros Define reporting requirements Dimensionally modeled relational SQLLeverage macro functions associated with Explore data sources to identify data generationsecurity access strategies Cross join SQLModel Maintenance and Extensibility Create a Baseline Project Various results sets for multi-fact queriesRemap metadata to another source Define a project and its structure Use Advanced ParameterizationImport and link a second data source Describe the Framework Manager Techniques in Framework MangerRun scripts to automate or update a model environment Leverage session, model, and customView lineage Create a baseline project parametersCreate a model report Enhance the model with additional Create prompt macrosOptimize and Tune Framework Manager metadata Leverage macro functions associated withModels Prepare Reusable Metadata securityWork in a Multi-Modeler Environment Ensure efficient filters by configuring Model Maintenance and ExtensibilitySegment and link a project prompt properties Remap metadata to another sourceBranch a project and merge results Model for Predictable Results: Identify Import and link a second data sourceManage OLAP Data Sources Reporting Issues Run scripts to automate or update a modelPublish an OLAP model Describe how IBM Cognos BI uses View lineagePublish a model with multiple OLAP data cardinality Create a model reportsources Identify reporting traps Optimize and Tune Framework ManagerPublish a model with an OLAP data source Use tools to analyze the model Modelsand a relational data source Model for Predictable Results: Virtual Work in a Multi-Modeler EnvironmentManage Framework Manager Packages Star Schemas Segment and link a projectControl model versioning Model in layers Branch a project and merge resultsNest packages Create aliases to avoid ambiguous joins Manage OLAP Data Sources

Merge query subjects to create as view Publish an OLAP modelbehavior Publish a model with multiple OLAP data

line Model for Predictable Results: sourcesDescribe IBM Cognos components Consolidate Metadata Publish a model with an OLAP data sourceDescribe IBM Cognos architecture at a high Create virtual dimensions to resolve and a relational data sourcelevel fact-to-fact joins Manage Framework Manager PackagesDefine IBM Cognos groups and roles Create a consolidated modeling layer for Control model versioningExplain how to extend IBM Cognos presentation purposes Nest packagesIdentify Common Data Structures Consolidate snowflake dimensions withExamine relationships and cardinality model query subjectsIdentify different data traps Simplify facts by hiding unnecessary lineExamine OLAP data sources codes Describe IBM Cognos componentsGather Requirements Calculations and Filters Describe IBM Cognos architecture at aDefine reporting requirements Use static filters to reduce the data high levelExplore data sources to identify data access returned Define IBM Cognos groups and rolesstrategies Use macros and parameters in Explain how to extend IBM CognosCreate a Baseline Project calculations and filters to dynamically Identify Common Data StructuresDefine a project and its structure control the data returned Examine relationships and cardinalityDescribe the Framework Manager Implement a Time Dimension Identify different data trapsenvironment Resolve confusion caused by multiple Examine OLAP data sourcesCreate a baseline project relationships between a time dimension Gather RequirementsEnhance the model with additional metadata and another table Define reporting requirementsPrepare Reusable Metadata Specify Determinants Explore data sources to identify dataEnsure efficient filters by configuring prompt Create the Presentation View access strategiesproperties Identify conformed vs. non-conformed Create a Baseline ProjectModel for Predictable Results: Identify dimensions Define a project and its structureReporting Issues Create star schema groupings to provide Describe the Framework ManagerDescribe how IBM Cognos BI uses authors with logical groupings of query environmentcardinality subjects Create a baseline projectIdentify reporting traps Work with Different Query Subject Types Enhance the model with additionalUse tools to analyze the model Identify the effects on generated SQL metadataModel for Predictable Results: Virtual Star when modifying query subjects, SQL Prepare Reusable MetadataSchemas settings and relationships Ensure efficient filters by configuringModel in layers Set Security in Framework Manager prompt propertiesCreate aliases to avoid ambiguous joins Restrict access to packages Model for Predictable Results: IdentifyMerge query subjects to create as view Create and apply security filters Reporting Issuesbehavior Restrict access to objects in the model Describe how IBM Cognos BI usesModel for Predictable Results: Consolidate Create Analysis Objects cardinalityMetadata Sort members for presentation and Identify reporting trapsCreate virtual dimensions to resolve predictability Use tools to analyze the modelfact-to-fact joins Manage MUNs in Framework Manager Model for Predictable Results: Virtual StarCreate a consolidated modeling layer for Define members and member unique Schemaspresentation purposes names Model in layers


Consolidate snowflake dimensions with Identify changes that impact a MUN Create aliases to avoid ambiguous joinsmodel query subjects Model for Drill Through in Framework Merge query subjects to create as viewSimplify facts by hiding unnecessary codes Manager behaviorCalculations and Filters Define a report drill through Model for Predictable Results: ConsolidateUse static filters to reduce the data returned Define a package-based drill through MetadataUse macros and parameters in calculations Identify drill-through values Create virtual dimensions to resolveand filters to dynamically control the data Advanced Generated SQL Concepts and fact-to-fact joinsreturned Complex Queries Create a consolidated modeling layer forImplement a Time Dimension Stitch query SQL presentation purposesResolve confusion caused by multiple Conformed and non-conformed Consolidate snowflake dimensions withrelationships between a time dimension and dimensions in generated SQL model query subjectsanother table Multi-fact/multi-grain stitch query SQL Simplify facts by hiding unnecessary codesSpecify Determinants Variances in Report Studio generated Calculations and FiltersCreate the Presentation View SQL Use static filters to reduce the dataIdentify conformed vs. non-conformed Dimensionally modeled relational SQL returneddimensions generation Use macros and parameters inCreate star schema groupings to provide Cross join SQL calculations and filters to dynamicallyauthors with logical groupings of query Various results sets for multi-fact queries control the data returnedsubjects Use Advanced Parameterization Implement a Time DimensionWork with Different Query Subject Types Techniques in Framework Manger Resolve confusion caused by multipleIdentify the effects on generated SQL when Leverage session, model, and custom relationships between a time dimensionmodifying query subjects, SQL settings and parameters and another tablerelationships Create prompt macros Specify DeterminantsSet Security in Framework Manager Leverage macro functions associated Create the Presentation ViewRestrict access to packages with security Identify conformed vs. non-conformedCreate and apply security filters Model Maintenance and Extensibility dimensionsRestrict access to objects in the model Remap metadata to another source Create star schema groupings to provideCreate Analysis Objects Import and link a second data source authors with logical groupings of querySort members for presentation and Run scripts to automate or update a subjectspredictability model Work with Different Query Subject TypesManage MUNs in Framework Manager View lineage Identify the effects on generated SQLDefine members and member unique names Create a model report when modifying query subjects, SQLIdentify changes that impact a MUN Optimize and Tune Framework Manager settings and relationshipsModel for Drill Through in Framework Models Set Security in Framework ManagerManager Work in a Multi-Modeler Environment Restrict access to packagesDefine a report drill through Segment and link a project Create and apply security filtersDefine a package-based drill through Branch a project and merge results Restrict access to objects in the modelIdentify drill-through values Manage OLAP Data Sources Create Analysis ObjectsAdvanced Generated SQL Concepts and Publish an OLAP model Sort members for presentation andComplex Queries Publish a model with multiple OLAP data predictabilityStitch query SQL sources Manage MUNs in Framework ManagerConformed and non-conformed dimensions Publish a model with an OLAP data Define members and member uniquein generated SQL source and a relational data source namesMulti-fact/multi-grain stitch query SQL Manage Framework Manager Packages Identify changes that impact a MUNVariances in Report Studio generated SQL Control model versioning Model for Drill Through in FrameworkDimensionally modeled relational SQL Nest packages Managergeneration Define a report drill throughCross join SQL Define a package-based drill throughVarious results sets for multi-fact queries line Identify drill-through valuesUse Advanced Parameterization Techniques Describe IBM Cognos components Advanced Generated SQL Concepts andin Framework Manger Describe IBM Cognos architecture at a Complex QueriesLeverage session, model, and custom high level Stitch query SQLparameters Define IBM Cognos groups and roles Conformed and non-conformedCreate prompt macros Explain how to extend IBM Cognos dimensions in generated SQLLeverage macro functions associated with Identify Common Data Structures Multi-fact/multi-grain stitch query SQLsecurity Examine relationships and cardinality Variances in Report Studio generated SQLModel Maintenance and Extensibility Identify different data traps Dimensionally modeled relational SQLRemap metadata to another source Examine OLAP data sources generationImport and link a second data source Gather Requirements Cross join SQLRun scripts to automate or update a model Define reporting requirements Various results sets for multi-fact queriesView lineage Explore data sources to identify data Use Advanced ParameterizationCreate a model report access strategies Techniques in Framework MangerOptimize and Tune Framework Manager Create a Baseline Project Leverage session, model, and customModels Define a project and its structure parametersWork in a Multi-Modeler Environment Describe the Framework Manager Create prompt macrosSegment and link a project environment Leverage macro functions associated with


Branch a project and merge results Create a baseline project securityManage OLAP Data Sources Enhance the model with additional Model Maintenance and ExtensibilityPublish an OLAP model metadata Remap metadata to another sourcePublish a model with multiple OLAP data Prepare Reusable Metadata Import and link a second data sourcesources Ensure efficient filters by configuring Run scripts to automate or update a modelPublish a model with an OLAP data source prompt properties View lineageand a relational data source Model for Predictable Results: Identify Create a model reportManage Framework Manager Packages Reporting Issues Optimize and Tune Framework ManagerControl model versioning Describe how IBM Cognos BI uses ModelsNest packages cardinality Work in a Multi-Modeler Environment

Identify reporting traps Segment and link a projectUse tools to analyze the model Branch a project and merge results

line Model for Predictable Results: Virtual Manage OLAP Data SourcesDescribe IBM Cognos components Star Schemas Publish an OLAP modelDescribe IBM Cognos architecture at a high Model in layers Publish a model with multiple OLAP datalevel Create aliases to avoid ambiguous joins sourcesDefine IBM Cognos groups and roles Merge query subjects to create as view Publish a model with an OLAP data sourceExplain how to extend IBM Cognos behavior and a relational data sourceIdentify Common Data Structures Model for Predictable Results: Manage Framework Manager PackagesExamine relationships and cardinality Consolidate Metadata Control model versioningIdentify different data traps Create virtual dimensions to resolve Nest packagesExamine OLAP data sources fact-to-fact joinsGather Requirements Create a consolidated modeling layer forDefine reporting requirements presentation purposes lineExplore data sources to identify data access Consolidate snowflake dimensions with Describe IBM Cognos componentsstrategies model query subjects Describe IBM Cognos architecture at aCreate a Baseline Project Simplify facts by hiding unnecessary high levelDefine a project and its structure codes Define IBM Cognos groups and rolesDescribe the Framework Manager Calculations and Filters Explain how to extend IBM Cognosenvironment Use static filters to reduce the data Identify Common Data StructuresCreate a baseline project returned Examine relationships and cardinalityEnhance the model with additional metadata Use macros and parameters in Identify different data trapsPrepare Reusable Metadata calculations and filters to dynamically Examine OLAP data sourcesEnsure efficient filters by configuring prompt control the data returned Gather Requirementsproperties Implement a Time Dimension Define reporting requirementsModel for Predictable Results: Identify Resolve confusion caused by multiple Explore data sources to identify dataReporting Issues relationships between a time dimension access strategiesDescribe how IBM Cognos BI uses and another table Create a Baseline Projectcardinality Specify Determinants Define a project and its structureIdentify reporting traps Create the Presentation View Describe the Framework ManagerUse tools to analyze the model Identify conformed vs. non-conformed environmentModel for Predictable Results: Virtual Star dimensions Create a baseline projectSchemas Create star schema groupings to provide Enhance the model with additionalModel in layers authors with logical groupings of query metadataCreate aliases to avoid ambiguous joins subjects Prepare Reusable MetadataMerge query subjects to create as view Work with Different Query Subject Types Ensure efficient filters by configuringbehavior Identify the effects on generated SQL prompt propertiesModel for Predictable Results: Consolidate when modifying query subjects, SQL Model for Predictable Results: IdentifyMetadata settings and relationships Reporting IssuesCreate virtual dimensions to resolve Set Security in Framework Manager Describe how IBM Cognos BI usesfact-to-fact joins Restrict access to packages cardinalityCreate a consolidated modeling layer for Create and apply security filters Identify reporting trapspresentation purposes Restrict access to objects in the model Use tools to analyze the modelConsolidate snowflake dimensions with Create Analysis Objects Model for Predictable Results: Virtual Starmodel query subjects Sort members for presentation and SchemasSimplify facts by hiding unnecessary codes predictability Model in layersCalculations and Filters Manage MUNs in Framework Manager Create aliases to avoid ambiguous joinsUse static filters to reduce the data returned Define members and member unique Merge query subjects to create as viewUse macros and parameters in calculations names behaviorand filters to dynamically control the data Identify changes that impact a MUN Model for Predictable Results: Consolidatereturned Model for Drill Through in Framework MetadataImplement a Time Dimension Manager Create virtual dimensions to resolveResolve confusion caused by multiple Define a report drill through fact-to-fact joinsrelationships between a time dimension and Define a package-based drill through Create a consolidated modeling layer foranother table Identify drill-through values presentation purposesSpecify Determinants Advanced Generated SQL Concepts and Consolidate snowflake dimensions with


Create the Presentation View Complex Queries model query subjectsIdentify conformed vs. non-conformed Stitch query SQL Simplify facts by hiding unnecessary codesdimensions Conformed and non-conformed Calculations and FiltersCreate star schema groupings to provide dimensions in generated SQL Use static filters to reduce the dataauthors with logical groupings of query Multi-fact/multi-grain stitch query SQL returnedsubjects Variances in Report Studio generated Use macros and parameters inWork with Different Query Subject Types SQL calculations and filters to dynamicallyIdentify the effects on generated SQL when Dimensionally modeled relational SQL control the data returnedmodifying query subjects, SQL settings and generation Implement a Time Dimensionrelationships Cross join SQL Resolve confusion caused by multipleSet Security in Framework Manager Various results sets for multi-fact queries relationships between a time dimensionRestrict access to packages Use Advanced Parameterization and another tableCreate and apply security filters Techniques in Framework Manger Specify DeterminantsRestrict access to objects in the model Leverage session, model, and custom Create the Presentation ViewCreate Analysis Objects parameters Identify conformed vs. non-conformedSort members for presentation and Create prompt macros dimensionspredictability Leverage macro functions associated Create star schema groupings to provideManage MUNs in Framework Manager with security authors with logical groupings of queryDefine members and member unique names Model Maintenance and Extensibility subjectsIdentify changes that impact a MUN Remap metadata to another source Work with Different Query Subject TypesModel for Drill Through in Framework Import and link a second data source Identify the effects on generated SQLManager Run scripts to automate or update a when modifying query subjects, SQLDefine a report drill through model settings and relationshipsDefine a package-based drill through View lineage Set Security in Framework ManagerIdentify drill-through values Create a model report Restrict access to packagesAdvanced Generated SQL Concepts and Optimize and Tune Framework Manager Create and apply security filtersComplex Queries Models Restrict access to objects in the modelStitch query SQL Work in a Multi-Modeler Environment Create Analysis ObjectsConformed and non-conformed dimensions Segment and link a project Sort members for presentation andin generated SQL Branch a project and merge results predictabilityMulti-fact/multi-grain stitch query SQL Manage OLAP Data Sources Manage MUNs in Framework ManagerVariances in Report Studio generated SQL Publish an OLAP model Define members and member uniqueDimensionally modeled relational SQL Publish a model with multiple OLAP data namesgeneration sources Identify changes that impact a MUNCross join SQL Publish a model with an OLAP data Model for Drill Through in FrameworkVarious results sets for multi-fact queries source and a relational data source ManagerUse Advanced Parameterization Techniques Manage Framework Manager Packages Define a report drill throughin Framework Manger Control model versioning Define a package-based drill throughLeverage session, model, and custom Nest packages Identify drill-through valuesparameters Advanced Generated SQL Concepts andCreate prompt macros Complex QueriesLeverage macro functions associated with line Stitch query SQLsecurity Discuss IBM Cognos and Performance Conformed and non-conformedModel Maintenance and Extensibility Management dimensions in generated SQLRemap metadata to another source Examine the characteristics of Multi-fact/multi-grain stitch query SQLImport and link a second data source operational databases and databases Variances in Report Studio generated SQLRun scripts to automate or update a model designed for reporting Dimensionally modeled relational SQLView lineage Examine key modeling recommendations generationCreate a model report Examine the IBM Cognos BI and Cross join SQLOptimize and Tune Framework Manager Framework Manager workflow processes Various results sets for multi-fact queriesModels Verify relationships and query item Use Advanced ParameterizationWork in a Multi-Modeler Environment properties Techniques in Framework MangerSegment and link a project Describe multi-fact queries and when full Leverage session, model, and customBranch a project and merge results outer joins are appropriate parametersManage OLAP Data Sources Identify the advantages of modeling Create prompt macrosPublish an OLAP model metadata as a star schema Leverage macro functions associated withPublish a model with multiple OLAP data Create virtual facts to simplify writing securitysources queries Model Maintenance and ExtensibilityPublish a model with an OLAP data source Use calculations to create Remap metadata to another sourceand a relational data source commonly-needed query items for Import and link a second data sourceManage Framework Manager Packages authors Run scripts to automate or update a modelControl model versioning Make time-based queries simple to View lineageNest packages author by implementing a time dimension Create a model report

Use determinants to specify multiple Optimize and Tune Framework Managerlevels of granularity and prevent Models

line double-counting Work in a Multi-Modeler Environment


Describe IBM Cognos components Identify the dimensions associated with a Segment and link a projectDescribe IBM Cognos architecture at a high fact table Branch a project and merge resultslevel Identify key differences and Manage OLAP Data SourcesDefine IBM Cognos groups and roles recommendations for using data source, Publish an OLAP modelExplain how to extend IBM Cognos model, and stored procedure query Publish a model with multiple OLAP dataIdentify Common Data Structures subjects sourcesExamine relationships and cardinality Examine the IBM Cognos BI security Publish a model with an OLAP data sourceIdentify different data traps environment and a relational data sourceExamine OLAP data sources Apply dimensional information to Manage Framework Manager PackagesGather Requirements relational Metadata to enable OLAP-style Control model versioningDefine reporting requirements queries Nest packagesExplore data sources to identify data access Describe model types and data entitiesstrategies Identify conformed values between dataCreate a Baseline Project sources lineDefine a project and its structure Governors that affect SQL generation Describe IBM Cognos componentsDescribe the Framework Manager Identify session and model parameters Describe IBM Cognos architecture at aenvironment Perform basic maintenance and high levelCreate a baseline project management on a model Define IBM Cognos groups and rolesEnhance the model with additional metadata Identify and implement techniques to Explain how to extend IBM CognosPrepare Reusable Metadata optimize and tune your Framework Identify Common Data StructuresEnsure efficient filters by configuring prompt Manager models Examine relationships and cardinalityproperties Implement repository control Identify different data trapsModel for Predictable Results: Identify Connect to an OLAP data source (cube) Examine OLAP data sourcesReporting Issues in a Framework Manager project Gather RequirementsDescribe how IBM Cognos BI uses Specify package languages and function Define reporting requirementscardinality sets Explore data sources to identify dataIdentify reporting traps access strategiesUse tools to analyze the model Create a Baseline ProjectModel for Predictable Results: Virtual Star line Define a project and its structureSchemas Describe IBM Cognos components Describe the Framework ManagerModel in layers Describe IBM Cognos architecture at a environmentCreate aliases to avoid ambiguous joins high level Create a baseline projectMerge query subjects to create as view Define IBM Cognos groups and roles Enhance the model with additionalbehavior Explain how to extend IBM Cognos metadataModel for Predictable Results: Consolidate Identify Common Data Structures Prepare Reusable MetadataMetadata Examine relationships and cardinality Ensure efficient filters by configuringCreate virtual dimensions to resolve Identify different data traps prompt propertiesfact-to-fact joins Examine OLAP data sources Model for Predictable Results: IdentifyCreate a consolidated modeling layer for Gather Requirements Reporting Issuespresentation purposes Define reporting requirements Describe how IBM Cognos BI usesConsolidate snowflake dimensions with Explore data sources to identify data cardinalitymodel query subjects access strategies Identify reporting trapsSimplify facts by hiding unnecessary codes Create a Baseline Project Use tools to analyze the modelCalculations and Filters Define a project and its structure Model for Predictable Results: Virtual StarUse static filters to reduce the data returned Describe the Framework Manager SchemasUse macros and parameters in calculations environment Model in layersand filters to dynamically control the data Create a baseline project Create aliases to avoid ambiguous joinsreturned Enhance the model with additional Merge query subjects to create as viewImplement a Time Dimension metadata behaviorResolve confusion caused by multiple Prepare Reusable Metadata Model for Predictable Results: Consolidaterelationships between a time dimension and Ensure efficient filters by configuring Metadataanother table prompt properties Create virtual dimensions to resolveSpecify Determinants Model for Predictable Results: Identify fact-to-fact joinsCreate the Presentation View Reporting Issues Create a consolidated modeling layer forIdentify conformed vs. non-conformed Describe how IBM Cognos BI uses presentation purposesdimensions cardinality Consolidate snowflake dimensions withCreate star schema groupings to provide Identify reporting traps model query subjectsauthors with logical groupings of query Use tools to analyze the model Simplify facts by hiding unnecessary codessubjects Model for Predictable Results: Virtual Calculations and FiltersWork with Different Query Subject Types Star Schemas Use static filters to reduce the dataIdentify the effects on generated SQL when Model in layers returnedmodifying query subjects, SQL settings and Create aliases to avoid ambiguous joins Use macros and parameters inrelationships Merge query subjects to create as view calculations and filters to dynamicallySet Security in Framework Manager behavior control the data returnedRestrict access to packages Model for Predictable Results: Implement a Time DimensionCreate and apply security filters Consolidate Metadata Resolve confusion caused by multiple


Restrict access to objects in the model Create virtual dimensions to resolve relationships between a time dimensionCreate Analysis Objects fact-to-fact joins and another tableSort members for presentation and Create a consolidated modeling layer for Specify Determinantspredictability presentation purposes Create the Presentation ViewManage MUNs in Framework Manager Consolidate snowflake dimensions with Identify conformed vs. non-conformedDefine members and member unique names model query subjects dimensionsIdentify changes that impact a MUN Simplify facts by hiding unnecessary Create star schema groupings to provideModel for Drill Through in Framework codes authors with logical groupings of queryManager Calculations and Filters subjectsDefine a report drill through Use static filters to reduce the data Work with Different Query Subject TypesDefine a package-based drill through returned Identify the effects on generated SQLIdentify drill-through values Use macros and parameters in when modifying query subjects, SQLAdvanced Generated SQL Concepts and calculations and filters to dynamically settings and relationshipsComplex Queries control the data returned Set Security in Framework ManagerStitch query SQL Implement a Time Dimension Restrict access to packagesConformed and non-conformed dimensions Resolve confusion caused by multiple Create and apply security filtersin generated SQL relationships between a time dimension Restrict access to objects in the modelMulti-fact/multi-grain stitch query SQL and another table Create Analysis ObjectsVariances in Report Studio generated SQL Specify Determinants Sort members for presentation andDimensionally modeled relational SQL Create the Presentation View predictabilitygeneration Identify conformed vs. non-conformed Manage MUNs in Framework ManagerCross join SQL dimensions Define members and member uniqueVarious results sets for multi-fact queries Create star schema groupings to provide namesUse Advanced Parameterization Techniques authors with logical groupings of query Identify changes that impact a MUNin Framework Manger subjects Model for Drill Through in FrameworkLeverage session, model, and custom Work with Different Query Subject Types Managerparameters Identify the effects on generated SQL Define a report drill throughCreate prompt macros when modifying query subjects, SQL Define a package-based drill throughLeverage macro functions associated with settings and relationships Identify drill-through valuessecurity Set Security in Framework Manager Advanced Generated SQL Concepts andModel Maintenance and Extensibility Restrict access to packages Complex QueriesRemap metadata to another source Create and apply security filters Stitch query SQLImport and link a second data source Restrict access to objects in the model Conformed and non-conformedRun scripts to automate or update a model Create Analysis Objects dimensions in generated SQLView lineage Sort members for presentation and Multi-fact/multi-grain stitch query SQLCreate a model report predictability Variances in Report Studio generated SQLOptimize and Tune Framework Manager Manage MUNs in Framework Manager Dimensionally modeled relational SQLModels Define members and member unique generationWork in a Multi-Modeler Environment names Cross join SQLSegment and link a project Identify changes that impact a MUN Various results sets for multi-fact queriesBranch a project and merge results Model for Drill Through in Framework Use Advanced ParameterizationManage OLAP Data Sources Manager Techniques in Framework MangerPublish an OLAP model Define a report drill through Leverage session, model, and customPublish a model with multiple OLAP data Define a package-based drill through parameterssources Identify drill-through values Create prompt macrosPublish a model with an OLAP data source Advanced Generated SQL Concepts and Leverage macro functions associated withand a relational data source Complex Queries securityManage Framework Manager Packages Stitch query SQL Model Maintenance and ExtensibilityControl model versioning Conformed and non-conformed Remap metadata to another sourceNest packages dimensions in generated SQL Import and link a second data source

Multi-fact/multi-grain stitch query SQL Run scripts to automate or update a modelVariances in Report Studio generated View lineage

line SQL Create a model reportDiscuss IBM Cognos and Performance Dimensionally modeled relational SQL Optimize and Tune Framework ManagerManagement generation ModelsExamine the characteristics of operational Cross join SQL Work in a Multi-Modeler Environmentdatabases and databases designed for Various results sets for multi-fact queries Segment and link a projectreporting Use Advanced Parameterization Branch a project and merge resultsExamine key modeling recommendations Techniques in Framework Manger Manage OLAP Data SourcesExamine the IBM Cognos BI and Framework Leverage session, model, and custom Publish an OLAP modelManager workflow processes parameters Publish a model with multiple OLAP dataVerify relationships and query item Create prompt macros sourcesproperties Leverage macro functions associated Publish a model with an OLAP data sourceDescribe multi-fact queries and when full with security and a relational data sourceouter joins are appropriate Model Maintenance and Extensibility Manage Framework Manager PackagesIdentify the advantages of modeling Remap metadata to another source Control model versioning


metadata as a star schema Import and link a second data source Nest packagesCreate virtual facts to simplify writing queries Run scripts to automate or update aUse calculations to create modelcommonly-needed query items for authors View lineage lineMake time-based queries simple to author Create a model report Describe IBM Cognos componentsby implementing a time dimension Optimize and Tune Framework Manager Describe IBM Cognos architecture at aUse determinants to specify multiple levels Models high levelof granularity and prevent double-counting Work in a Multi-Modeler Environment Define IBM Cognos groups and rolesIdentify the dimensions associated with a Segment and link a project Explain how to extend IBM Cognosfact table Branch a project and merge results Identify Common Data StructuresIdentify key differences and Manage OLAP Data Sources Examine relationships and cardinalityrecommendations for using data source, Publish an OLAP model Identify different data trapsmodel, and stored procedure query subjects Publish a model with multiple OLAP data Examine OLAP data sourcesExamine the IBM Cognos BI security sources Gather Requirementsenvironment Publish a model with an OLAP data Define reporting requirementsApply dimensional information to relational source and a relational data source Explore data sources to identify dataMetadata to enable OLAP-style queries Manage Framework Manager Packages access strategiesDescribe model types and data entities Control model versioning Create a Baseline ProjectIdentify conformed values between data Nest packages Define a project and its structuresources Describe the Framework ManagerGovernors that affect SQL generation environmentIdentify session and model parameters line Create a baseline projectPerform basic maintenance and Describe IBM Cognos components Enhance the model with additionalmanagement on a model Describe IBM Cognos architecture at a metadataIdentify and implement techniques to high level Prepare Reusable Metadataoptimize and tune your Framework Manager Define IBM Cognos groups and roles Ensure efficient filters by configuringmodels Explain how to extend IBM Cognos prompt propertiesImplement repository control Identify Common Data Structures Model for Predictable Results: IdentifyConnect to an OLAP data source (cube) in a Examine relationships and cardinality Reporting IssuesFramework Manager project Identify different data traps Describe how IBM Cognos BI usesSpecify package languages and function Examine OLAP data sources cardinalitysets Gather Requirements Identify reporting traps

Define reporting requirements Use tools to analyze the modelExplore data sources to identify data Model for Predictable Results: Virtual Star

line access strategies SchemasDescribe IBM Cognos components Create a Baseline Project Model in layersDescribe IBM Cognos architecture at a high Define a project and its structure Create aliases to avoid ambiguous joinslevel Describe the Framework Manager Merge query subjects to create as viewDefine IBM Cognos groups and roles environment behaviorExplain how to extend IBM Cognos Create a baseline project Model for Predictable Results: ConsolidateIdentify Common Data Structures Enhance the model with additional MetadataExamine relationships and cardinality metadata Create virtual dimensions to resolveIdentify different data traps Prepare Reusable Metadata fact-to-fact joinsExamine OLAP data sources Ensure efficient filters by configuring Create a consolidated modeling layer forGather Requirements prompt properties presentation purposesDefine reporting requirements Model for Predictable Results: Identify Consolidate snowflake dimensions withExplore data sources to identify data access Reporting Issues model query subjectsstrategies Describe how IBM Cognos BI uses Simplify facts by hiding unnecessary codesCreate a Baseline Project cardinality Calculations and FiltersDefine a project and its structure Identify reporting traps Use static filters to reduce the dataDescribe the Framework Manager Use tools to analyze the model returnedenvironment Model for Predictable Results: Virtual Use macros and parameters inCreate a baseline project Star Schemas calculations and filters to dynamicallyEnhance the model with additional metadata Model in layers control the data returnedPrepare Reusable Metadata Create aliases to avoid ambiguous joins Implement a Time DimensionEnsure efficient filters by configuring prompt Merge query subjects to create as view Resolve confusion caused by multipleproperties behavior relationships between a time dimensionModel for Predictable Results: Identify Model for Predictable Results: and another tableReporting Issues Consolidate Metadata Specify DeterminantsDescribe how IBM Cognos BI uses Create virtual dimensions to resolve Create the Presentation Viewcardinality fact-to-fact joins Identify conformed vs. non-conformedIdentify reporting traps Create a consolidated modeling layer for dimensionsUse tools to analyze the model presentation purposes Create star schema groupings to provideModel for Predictable Results: Virtual Star Consolidate snowflake dimensions with authors with logical groupings of querySchemas model query subjects subjectsModel in layers Simplify facts by hiding unnecessary Work with Different Query Subject Types


Create aliases to avoid ambiguous joins codes Identify the effects on generated SQLMerge query subjects to create as view Calculations and Filters when modifying query subjects, SQLbehavior Use static filters to reduce the data settings and relationshipsModel for Predictable Results: Consolidate returned Set Security in Framework ManagerMetadata Use macros and parameters in Restrict access to packagesCreate virtual dimensions to resolve calculations and filters to dynamically Create and apply security filtersfact-to-fact joins control the data returned Restrict access to objects in the modelCreate a consolidated modeling layer for Implement a Time Dimension Create Analysis Objectspresentation purposes Resolve confusion caused by multiple Sort members for presentation andConsolidate snowflake dimensions with relationships between a time dimension predictabilitymodel query subjects and another table Manage MUNs in Framework ManagerSimplify facts by hiding unnecessary codes Specify Determinants Define members and member uniqueCalculations and Filters Create the Presentation View namesUse static filters to reduce the data returned Identify conformed vs. non-conformed Identify changes that impact a MUNUse macros and parameters in calculations dimensions Model for Drill Through in Frameworkand filters to dynamically control the data Create star schema groupings to provide Managerreturned authors with logical groupings of query Define a report drill throughImplement a Time Dimension subjects Define a package-based drill throughResolve confusion caused by multiple Work with Different Query Subject Types Identify drill-through valuesrelationships between a time dimension and Identify the effects on generated SQL Advanced Generated SQL Concepts andanother table when modifying query subjects, SQL Complex QueriesSpecify Determinants settings and relationships Stitch query SQLCreate the Presentation View Set Security in Framework Manager Conformed and non-conformedIdentify conformed vs. non-conformed Restrict access to packages dimensions in generated SQLdimensions Create and apply security filters Multi-fact/multi-grain stitch query SQLCreate star schema groupings to provide Restrict access to objects in the model Variances in Report Studio generated SQLauthors with logical groupings of query Create Analysis Objects Dimensionally modeled relational SQLsubjects Sort members for presentation and generationWork with Different Query Subject Types predictability Cross join SQLIdentify the effects on generated SQL when Manage MUNs in Framework Manager Various results sets for multi-fact queriesmodifying query subjects, SQL settings and Define members and member unique Use Advanced Parameterizationrelationships names Techniques in Framework MangerSet Security in Framework Manager Identify changes that impact a MUN Leverage session, model, and customRestrict access to packages Model for Drill Through in Framework parametersCreate and apply security filters Manager Create prompt macrosRestrict access to objects in the model Define a report drill through Leverage macro functions associated withCreate Analysis Objects Define a package-based drill through securitySort members for presentation and Identify drill-through values Model Maintenance and Extensibilitypredictability Advanced Generated SQL Concepts and Remap metadata to another sourceManage MUNs in Framework Manager Complex Queries Import and link a second data sourceDefine members and member unique names Stitch query SQL Run scripts to automate or update a modelIdentify changes that impact a MUN Conformed and non-conformed View lineageModel for Drill Through in Framework dimensions in generated SQL Create a model reportManager Multi-fact/multi-grain stitch query SQL Optimize and Tune Framework ManagerDefine a report drill through Variances in Report Studio generated ModelsDefine a package-based drill through SQL Work in a Multi-Modeler EnvironmentIdentify drill-through values Dimensionally modeled relational SQL Segment and link a projectAdvanced Generated SQL Concepts and generation Branch a project and merge resultsComplex Queries Cross join SQL Manage OLAP Data SourcesStitch query SQL Various results sets for multi-fact queries Publish an OLAP modelConformed and non-conformed dimensions Use Advanced Parameterization Publish a model with multiple OLAP datain generated SQL Techniques in Framework Manger sourcesMulti-fact/multi-grain stitch query SQL Leverage session, model, and custom Publish a model with an OLAP data sourceVariances in Report Studio generated SQL parameters and a relational data sourceDimensionally modeled relational SQL Create prompt macros Manage Framework Manager Packagesgeneration Leverage macro functions associated Control model versioningCross join SQL with security Nest packagesVarious results sets for multi-fact queries Model Maintenance and ExtensibilityUse Advanced Parameterization Techniques Remap metadata to another sourcein Framework Manger Import and link a second data source lineLeverage session, model, and custom Run scripts to automate or update a Describe IBM Cognos componentsparameters model Describe IBM Cognos architecture at aCreate prompt macros View lineage high levelLeverage macro functions associated with Create a model report Define IBM Cognos groups and rolessecurity Optimize and Tune Framework Manager Explain how to extend IBM CognosModel Maintenance and Extensibility Models Identify Common Data Structures


Remap metadata to another source Work in a Multi-Modeler Environment Examine relationships and cardinalityImport and link a second data source Segment and link a project Identify different data trapsRun scripts to automate or update a model Branch a project and merge results Examine OLAP data sourcesView lineage Manage OLAP Data Sources Gather RequirementsCreate a model report Publish an OLAP model Define reporting requirementsOptimize and Tune Framework Manager Publish a model with multiple OLAP data Explore data sources to identify dataModels sources access strategiesWork in a Multi-Modeler Environment Publish a model with an OLAP data Create a Baseline ProjectSegment and link a project source and a relational data source Define a project and its structureBranch a project and merge results Manage Framework Manager Packages Describe the Framework ManagerManage OLAP Data Sources Control model versioning environmentPublish an OLAP model Nest packages Create a baseline projectPublish a model with multiple OLAP data Enhance the model with additionalsources metadataPublish a model with an OLAP data source line Prepare Reusable Metadataand a relational data source Describe IBM Cognos components Ensure efficient filters by configuringManage Framework Manager Packages Describe IBM Cognos architecture at a prompt propertiesControl model versioning high level Model for Predictable Results: IdentifyNest packages Define IBM Cognos groups and roles Reporting Issues

Explain how to extend IBM Cognos Describe how IBM Cognos BI usesIdentify Common Data Structures cardinality

line Examine relationships and cardinality Identify reporting trapsDescribe IBM Cognos components Identify different data traps Use tools to analyze the modelDescribe IBM Cognos architecture at a high Examine OLAP data sources Model for Predictable Results: Virtual Starlevel Gather Requirements SchemasDefine IBM Cognos groups and roles Define reporting requirements Model in layersExplain how to extend IBM Cognos Explore data sources to identify data Create aliases to avoid ambiguous joinsIdentify Common Data Structures access strategies Merge query subjects to create as viewExamine relationships and cardinality Create a Baseline Project behaviorIdentify different data traps Define a project and its structure Model for Predictable Results: ConsolidateExamine OLAP data sources Describe the Framework Manager MetadataGather Requirements environment Create virtual dimensions to resolveDefine reporting requirements Create a baseline project fact-to-fact joinsExplore data sources to identify data access Enhance the model with additional Create a consolidated modeling layer forstrategies metadata presentation purposesCreate a Baseline Project Prepare Reusable Metadata Consolidate snowflake dimensions withDefine a project and its structure Ensure efficient filters by configuring model query subjectsDescribe the Framework Manager prompt properties Simplify facts by hiding unnecessary codesenvironment Model for Predictable Results: Identify Calculations and FiltersCreate a baseline project Reporting Issues Use static filters to reduce the dataEnhance the model with additional metadata Describe how IBM Cognos BI uses returnedPrepare Reusable Metadata cardinality Use macros and parameters inEnsure efficient filters by configuring prompt Identify reporting traps calculations and filters to dynamicallyproperties Use tools to analyze the model control the data returnedModel for Predictable Results: Identify Model for Predictable Results: Virtual Implement a Time DimensionReporting Issues Star Schemas Resolve confusion caused by multipleDescribe how IBM Cognos BI uses Model in layers relationships between a time dimensioncardinality Create aliases to avoid ambiguous joins and another tableIdentify reporting traps Merge query subjects to create as view Specify DeterminantsUse tools to analyze the model behavior Create the Presentation ViewModel for Predictable Results: Virtual Star Model for Predictable Results: Identify conformed vs. non-conformedSchemas Consolidate Metadata dimensionsModel in layers Create virtual dimensions to resolve Create star schema groupings to provideCreate aliases to avoid ambiguous joins fact-to-fact joins authors with logical groupings of queryMerge query subjects to create as view Create a consolidated modeling layer for subjectsbehavior presentation purposes Work with Different Query Subject TypesModel for Predictable Results: Consolidate Consolidate snowflake dimensions with Identify the effects on generated SQLMetadata model query subjects when modifying query subjects, SQLCreate virtual dimensions to resolve Simplify facts by hiding unnecessary settings and relationshipsfact-to-fact joins codes Set Security in Framework ManagerCreate a consolidated modeling layer for Calculations and Filters Restrict access to packagespresentation purposes Use static filters to reduce the data Create and apply security filtersConsolidate snowflake dimensions with returned Restrict access to objects in the modelmodel query subjects Use macros and parameters in Create Analysis ObjectsSimplify facts by hiding unnecessary codes calculations and filters to dynamically Sort members for presentation andCalculations and Filters control the data returned predictability


Use static filters to reduce the data returned Implement a Time Dimension Manage MUNs in Framework ManagerUse macros and parameters in calculations Resolve confusion caused by multiple Define members and member uniqueand filters to dynamically control the data relationships between a time dimension namesreturned and another table Identify changes that impact a MUNImplement a Time Dimension Specify Determinants Model for Drill Through in FrameworkResolve confusion caused by multiple Create the Presentation View Managerrelationships between a time dimension and Identify conformed vs. non-conformed Define a report drill throughanother table dimensions Define a package-based drill throughSpecify Determinants Create star schema groupings to provide Identify drill-through valuesCreate the Presentation View authors with logical groupings of query Advanced Generated SQL Concepts andIdentify conformed vs. non-conformed subjects Complex Queriesdimensions Work with Different Query Subject Types Stitch query SQLCreate star schema groupings to provide Identify the effects on generated SQL Conformed and non-conformedauthors with logical groupings of query when modifying query subjects, SQL dimensions in generated SQLsubjects settings and relationships Multi-fact/multi-grain stitch query SQLWork with Different Query Subject Types Set Security in Framework Manager Variances in Report Studio generated SQLIdentify the effects on generated SQL when Restrict access to packages Dimensionally modeled relational SQLmodifying query subjects, SQL settings and Create and apply security filters generationrelationships Restrict access to objects in the model Cross join SQLSet Security in Framework Manager Create Analysis Objects Various results sets for multi-fact queriesRestrict access to packages Sort members for presentation and Use Advanced ParameterizationCreate and apply security filters predictability Techniques in Framework MangerRestrict access to objects in the model Manage MUNs in Framework Manager Leverage session, model, and customCreate Analysis Objects Define members and member unique parametersSort members for presentation and names Create prompt macrospredictability Identify changes that impact a MUN Leverage macro functions associated withManage MUNs in Framework Manager Model for Drill Through in Framework securityDefine members and member unique names Manager Model Maintenance and ExtensibilityIdentify changes that impact a MUN Define a report drill through Remap metadata to another sourceModel for Drill Through in Framework Define a package-based drill through Import and link a second data sourceManager Identify drill-through values Run scripts to automate or update a modelDefine a report drill through Advanced Generated SQL Concepts and View lineageDefine a package-based drill through Complex Queries Create a model reportIdentify drill-through values Stitch query SQL Optimize and Tune Framework ManagerAdvanced Generated SQL Concepts and Conformed and non-conformed ModelsComplex Queries dimensions in generated SQL Work in a Multi-Modeler EnvironmentStitch query SQL Multi-fact/multi-grain stitch query SQL Segment and link a projectConformed and non-conformed dimensions Variances in Report Studio generated Branch a project and merge resultsin generated SQL SQL Manage OLAP Data SourcesMulti-fact/multi-grain stitch query SQL Dimensionally modeled relational SQL Publish an OLAP modelVariances in Report Studio generated SQL generation Publish a model with multiple OLAP dataDimensionally modeled relational SQL Cross join SQL sourcesgeneration Various results sets for multi-fact queries Publish a model with an OLAP data sourceCross join SQL Use Advanced Parameterization and a relational data sourceVarious results sets for multi-fact queries Techniques in Framework Manger Manage Framework Manager PackagesUse Advanced Parameterization Techniques Leverage session, model, and custom Control model versioningin Framework Manger parameters Nest packagesLeverage session, model, and custom Create prompt macrosparameters Leverage macro functions associatedCreate prompt macros with security lineLeverage macro functions associated with Model Maintenance and Extensibility Describe IBM Cognos componentssecurity Remap metadata to another source Describe IBM Cognos architecture at aModel Maintenance and Extensibility Import and link a second data source high levelRemap metadata to another source Run scripts to automate or update a Define IBM Cognos groups and rolesImport and link a second data source model Explain how to extend IBM CognosRun scripts to automate or update a model View lineage Identify Common Data StructuresView lineage Create a model report Examine relationships and cardinalityCreate a model report Optimize and Tune Framework Manager Identify different data trapsOptimize and Tune Framework Manager Models Examine OLAP data sourcesModels Work in a Multi-Modeler Environment Gather RequirementsWork in a Multi-Modeler Environment Segment and link a project Define reporting requirementsSegment and link a project Branch a project and merge results Explore data sources to identify dataBranch a project and merge results Manage OLAP Data Sources access strategiesManage OLAP Data Sources Publish an OLAP model Create a Baseline ProjectPublish an OLAP model Publish a model with multiple OLAP data Define a project and its structurePublish a model with multiple OLAP data sources Describe the Framework Manager


sources Publish a model with an OLAP data environmentPublish a model with an OLAP data source source and a relational data source Create a baseline projectand a relational data source Manage Framework Manager Packages Enhance the model with additionalManage Framework Manager Packages Control model versioning metadataControl model versioning Nest packages Prepare Reusable MetadataNest packages Ensure efficient filters by configuring

prompt propertiesline Model for Predictable Results: Identify

line Discuss IBM Cognos and Performance Reporting IssuesDescribe IBM Cognos components Management Describe how IBM Cognos BI usesDescribe IBM Cognos architecture at a high Examine the characteristics of cardinalitylevel operational databases and databases Identify reporting trapsDefine IBM Cognos groups and roles designed for reporting Use tools to analyze the modelExplain how to extend IBM Cognos Examine key modeling recommendations Model for Predictable Results: Virtual StarIdentify Common Data Structures Examine the IBM Cognos BI and SchemasExamine relationships and cardinality Framework Manager workflow processes Model in layersIdentify different data traps Verify relationships and query item Create aliases to avoid ambiguous joinsExamine OLAP data sources properties Merge query subjects to create as viewGather Requirements Describe multi-fact queries and when full behaviorDefine reporting requirements outer joins are appropriate Model for Predictable Results: ConsolidateExplore data sources to identify data access Identify the advantages of modeling Metadatastrategies metadata as a star schema Create virtual dimensions to resolveCreate a Baseline Project Create virtual facts to simplify writing fact-to-fact joinsDefine a project and its structure queries Create a consolidated modeling layer forDescribe the Framework Manager Use calculations to create presentation purposesenvironment commonly-needed query items for Consolidate snowflake dimensions withCreate a baseline project authors model query subjectsEnhance the model with additional metadata Make time-based queries simple to Simplify facts by hiding unnecessary codesPrepare Reusable Metadata author by implementing a time dimension Calculations and FiltersEnsure efficient filters by configuring prompt Use determinants to specify multiple Use static filters to reduce the dataproperties levels of granularity and prevent returnedModel for Predictable Results: Identify double-counting Use macros and parameters inReporting Issues Identify the dimensions associated with a calculations and filters to dynamicallyDescribe how IBM Cognos BI uses fact table control the data returnedcardinality Identify key differences and Implement a Time DimensionIdentify reporting traps recommendations for using data source, Resolve confusion caused by multipleUse tools to analyze the model model, and stored procedure query relationships between a time dimensionModel for Predictable Results: Virtual Star subjects and another tableSchemas Examine the IBM Cognos BI security Specify DeterminantsModel in layers environment Create the Presentation ViewCreate aliases to avoid ambiguous joins Apply dimensional information to Identify conformed vs. non-conformedMerge query subjects to create as view relational Metadata to enable OLAP-style dimensionsbehavior queries Create star schema groupings to provideModel for Predictable Results: Consolidate Describe model types and data entities authors with logical groupings of queryMetadata Identify conformed values between data subjectsCreate virtual dimensions to resolve sources Work with Different Query Subject Typesfact-to-fact joins Governors that affect SQL generation Identify the effects on generated SQLCreate a consolidated modeling layer for Identify session and model parameters when modifying query subjects, SQLpresentation purposes Perform basic maintenance and settings and relationshipsConsolidate snowflake dimensions with management on a model Set Security in Framework Managermodel query subjects Identify and implement techniques to Restrict access to packagesSimplify facts by hiding unnecessary codes optimize and tune your Framework Create and apply security filtersCalculations and Filters Manager models Restrict access to objects in the modelUse static filters to reduce the data returned Implement repository control Create Analysis ObjectsUse macros and parameters in calculations Connect to an OLAP data source (cube) Sort members for presentation andand filters to dynamically control the data in a Framework Manager project predictabilityreturned Specify package languages and function Manage MUNs in Framework ManagerImplement a Time Dimension sets Define members and member uniqueResolve confusion caused by multiple namesrelationships between a time dimension and Identify changes that impact a MUNanother table line Model for Drill Through in FrameworkSpecify Determinants Describe IBM Cognos components ManagerCreate the Presentation View Describe IBM Cognos architecture at a Define a report drill throughIdentify conformed vs. non-conformed high level Define a package-based drill throughdimensions Define IBM Cognos groups and roles Identify drill-through valuesCreate star schema groupings to provide Explain how to extend IBM Cognos Advanced Generated SQL Concepts and


authors with logical groupings of query Identify Common Data Structures Complex Queriessubjects Examine relationships and cardinality Stitch query SQLWork with Different Query Subject Types Identify different data traps Conformed and non-conformedIdentify the effects on generated SQL when Examine OLAP data sources dimensions in generated SQLmodifying query subjects, SQL settings and Gather Requirements Multi-fact/multi-grain stitch query SQLrelationships Define reporting requirements Variances in Report Studio generated SQLSet Security in Framework Manager Explore data sources to identify data Dimensionally modeled relational SQLRestrict access to packages access strategies generationCreate and apply security filters Create a Baseline Project Cross join SQLRestrict access to objects in the model Define a project and its structure Various results sets for multi-fact queriesCreate Analysis Objects Describe the Framework Manager Use Advanced ParameterizationSort members for presentation and environment Techniques in Framework Mangerpredictability Create a baseline project Leverage session, model, and customManage MUNs in Framework Manager Enhance the model with additional parametersDefine members and member unique names metadata Create prompt macrosIdentify changes that impact a MUN Prepare Reusable Metadata Leverage macro functions associated withModel for Drill Through in Framework Ensure efficient filters by configuring securityManager prompt properties Model Maintenance and ExtensibilityDefine a report drill through Model for Predictable Results: Identify Remap metadata to another sourceDefine a package-based drill through Reporting Issues Import and link a second data sourceIdentify drill-through values Describe how IBM Cognos BI uses Run scripts to automate or update a modelAdvanced Generated SQL Concepts and cardinality View lineageComplex Queries Identify reporting traps Create a model reportStitch query SQL Use tools to analyze the model Optimize and Tune Framework ManagerConformed and non-conformed dimensions Model for Predictable Results: Virtual Modelsin generated SQL Star Schemas Work in a Multi-Modeler EnvironmentMulti-fact/multi-grain stitch query SQL Model in layers Segment and link a projectVariances in Report Studio generated SQL Create aliases to avoid ambiguous joins Branch a project and merge resultsDimensionally modeled relational SQL Merge query subjects to create as view Manage OLAP Data Sourcesgeneration behavior Publish an OLAP modelCross join SQL Model for Predictable Results: Publish a model with multiple OLAP dataVarious results sets for multi-fact queries Consolidate Metadata sourcesUse Advanced Parameterization Techniques Create virtual dimensions to resolve Publish a model with an OLAP data sourcein Framework Manger fact-to-fact joins and a relational data sourceLeverage session, model, and custom Create a consolidated modeling layer for Manage Framework Manager Packagesparameters presentation purposes Control model versioningCreate prompt macros Consolidate snowflake dimensions with Nest packagesLeverage macro functions associated with model query subjectssecurity Simplify facts by hiding unnecessaryModel Maintenance and Extensibility codes lineRemap metadata to another source Calculations and Filters Describe IBM Cognos componentsImport and link a second data source Use static filters to reduce the data Describe IBM Cognos architecture at aRun scripts to automate or update a model returned high levelView lineage Use macros and parameters in Define IBM Cognos groups and rolesCreate a model report calculations and filters to dynamically Explain how to extend IBM CognosOptimize and Tune Framework Manager control the data returned Identify Common Data StructuresModels Implement a Time Dimension Examine relationships and cardinalityWork in a Multi-Modeler Environment Resolve confusion caused by multiple Identify different data trapsSegment and link a project relationships between a time dimension Examine OLAP data sourcesBranch a project and merge results and another table Gather RequirementsManage OLAP Data Sources Specify Determinants Define reporting requirementsPublish an OLAP model Create the Presentation View Explore data sources to identify dataPublish a model with multiple OLAP data Identify conformed vs. non-conformed access strategiessources dimensions Create a Baseline ProjectPublish a model with an OLAP data source Create star schema groupings to provide Define a project and its structureand a relational data source authors with logical groupings of query Describe the Framework ManagerManage Framework Manager Packages subjects environmentControl model versioning Work with Different Query Subject Types Create a baseline projectNest packages Identify the effects on generated SQL Enhance the model with additional

when modifying query subjects, SQL metadatasettings and relationships Prepare Reusable Metadata

line Set Security in Framework Manager Ensure efficient filters by configuringDescribe IBM Cognos components Restrict access to packages prompt propertiesDescribe IBM Cognos architecture at a high Create and apply security filters Model for Predictable Results: Identifylevel Restrict access to objects in the model Reporting IssuesDefine IBM Cognos groups and roles Create Analysis Objects Describe how IBM Cognos BI uses


Explain how to extend IBM Cognos Sort members for presentation and cardinalityIdentify Common Data Structures predictability Identify reporting trapsExamine relationships and cardinality Manage MUNs in Framework Manager Use tools to analyze the modelIdentify different data traps Define members and member unique Model for Predictable Results: Virtual StarExamine OLAP data sources names SchemasGather Requirements Identify changes that impact a MUN Model in layersDefine reporting requirements Model for Drill Through in Framework Create aliases to avoid ambiguous joinsExplore data sources to identify data access Manager Merge query subjects to create as viewstrategies Define a report drill through behaviorCreate a Baseline Project Define a package-based drill through Model for Predictable Results: ConsolidateDefine a project and its structure Identify drill-through values MetadataDescribe the Framework Manager Advanced Generated SQL Concepts and Create virtual dimensions to resolveenvironment Complex Queries fact-to-fact joinsCreate a baseline project Stitch query SQL Create a consolidated modeling layer forEnhance the model with additional metadata Conformed and non-conformed presentation purposesPrepare Reusable Metadata dimensions in generated SQL Consolidate snowflake dimensions withEnsure efficient filters by configuring prompt Multi-fact/multi-grain stitch query SQL model query subjectsproperties Variances in Report Studio generated Simplify facts by hiding unnecessary codesModel for Predictable Results: Identify SQL Calculations and FiltersReporting Issues Dimensionally modeled relational SQL Use static filters to reduce the dataDescribe how IBM Cognos BI uses generation returnedcardinality Cross join SQL Use macros and parameters inIdentify reporting traps Various results sets for multi-fact queries calculations and filters to dynamicallyUse tools to analyze the model Use Advanced Parameterization control the data returnedModel for Predictable Results: Virtual Star Techniques in Framework Manger Implement a Time DimensionSchemas Leverage session, model, and custom Resolve confusion caused by multipleModel in layers parameters relationships between a time dimensionCreate aliases to avoid ambiguous joins Create prompt macros and another tableMerge query subjects to create as view Leverage macro functions associated Specify Determinantsbehavior with security Create the Presentation ViewModel for Predictable Results: Consolidate Model Maintenance and Extensibility Identify conformed vs. non-conformedMetadata Remap metadata to another source dimensionsCreate virtual dimensions to resolve Import and link a second data source Create star schema groupings to providefact-to-fact joins Run scripts to automate or update a authors with logical groupings of queryCreate a consolidated modeling layer for model subjectspresentation purposes View lineage Work with Different Query Subject TypesConsolidate snowflake dimensions with Create a model report Identify the effects on generated SQLmodel query subjects Optimize and Tune Framework Manager when modifying query subjects, SQLSimplify facts by hiding unnecessary codes Models settings and relationshipsCalculations and Filters Work in a Multi-Modeler Environment Set Security in Framework ManagerUse static filters to reduce the data returned Segment and link a project Restrict access to packagesUse macros and parameters in calculations Branch a project and merge results Create and apply security filtersand filters to dynamically control the data Manage OLAP Data Sources Restrict access to objects in the modelreturned Publish an OLAP model Create Analysis ObjectsImplement a Time Dimension Publish a model with multiple OLAP data Sort members for presentation andResolve confusion caused by multiple sources predictabilityrelationships between a time dimension and Publish a model with an OLAP data Manage MUNs in Framework Manageranother table source and a relational data source Define members and member uniqueSpecify Determinants Manage Framework Manager Packages namesCreate the Presentation View Control model versioning Identify changes that impact a MUNIdentify conformed vs. non-conformed Nest packages Model for Drill Through in Frameworkdimensions ManagerCreate star schema groupings to provide Define a report drill throughauthors with logical groupings of query line Define a package-based drill throughsubjects Describe IBM Cognos components Identify drill-through valuesWork with Different Query Subject Types Describe IBM Cognos architecture at a Advanced Generated SQL Concepts andIdentify the effects on generated SQL when high level Complex Queriesmodifying query subjects, SQL settings and Define IBM Cognos groups and roles Stitch query SQLrelationships Explain how to extend IBM Cognos Conformed and non-conformedSet Security in Framework Manager Identify Common Data Structures dimensions in generated SQLRestrict access to packages Examine relationships and cardinality Multi-fact/multi-grain stitch query SQLCreate and apply security filters Identify different data traps Variances in Report Studio generated SQLRestrict access to objects in the model Examine OLAP data sources Dimensionally modeled relational SQLCreate Analysis Objects Gather Requirements generationSort members for presentation and Define reporting requirements Cross join SQLpredictability Explore data sources to identify data Various results sets for multi-fact queries


Manage MUNs in Framework Manager access strategies Use Advanced ParameterizationDefine members and member unique names Create a Baseline Project Techniques in Framework MangerIdentify changes that impact a MUN Define a project and its structure Leverage session, model, and customModel for Drill Through in Framework Describe the Framework Manager parametersManager environment Create prompt macrosDefine a report drill through Create a baseline project Leverage macro functions associated withDefine a package-based drill through Enhance the model with additional securityIdentify drill-through values metadata Model Maintenance and ExtensibilityAdvanced Generated SQL Concepts and Prepare Reusable Metadata Remap metadata to another sourceComplex Queries Ensure efficient filters by configuring Import and link a second data sourceStitch query SQL prompt properties Run scripts to automate or update a modelConformed and non-conformed dimensions Model for Predictable Results: Identify View lineagein generated SQL Reporting Issues Create a model reportMulti-fact/multi-grain stitch query SQL Describe how IBM Cognos BI uses Optimize and Tune Framework ManagerVariances in Report Studio generated SQL cardinality ModelsDimensionally modeled relational SQL Identify reporting traps Work in a Multi-Modeler Environmentgeneration Use tools to analyze the model Segment and link a projectCross join SQL Model for Predictable Results: Virtual Branch a project and merge resultsVarious results sets for multi-fact queries Star Schemas Manage OLAP Data SourcesUse Advanced Parameterization Techniques Model in layers Publish an OLAP modelin Framework Manger Create aliases to avoid ambiguous joins Publish a model with multiple OLAP dataLeverage session, model, and custom Merge query subjects to create as view sourcesparameters behavior Publish a model with an OLAP data sourceCreate prompt macros Model for Predictable Results: and a relational data sourceLeverage macro functions associated with Consolidate Metadata Manage Framework Manager Packagessecurity Create virtual dimensions to resolve Control model versioningModel Maintenance and Extensibility fact-to-fact joins Nest packagesRemap metadata to another source Create a consolidated modeling layer forImport and link a second data source presentation purposesRun scripts to automate or update a model Consolidate snowflake dimensions with lineView lineage model query subjects Discuss IBM Cognos and PerformanceCreate a model report Simplify facts by hiding unnecessary ManagementOptimize and Tune Framework Manager codes Examine the characteristics of operationalModels Calculations and Filters databases and databases designed forWork in a Multi-Modeler Environment Use static filters to reduce the data reportingSegment and link a project returned Examine key modeling recommendationsBranch a project and merge results Use macros and parameters in Examine the IBM Cognos BI andManage OLAP Data Sources calculations and filters to dynamically Framework Manager workflow processesPublish an OLAP model control the data returned Verify relationships and query itemPublish a model with multiple OLAP data Implement a Time Dimension propertiessources Resolve confusion caused by multiple Describe multi-fact queries and when fullPublish a model with an OLAP data source relationships between a time dimension outer joins are appropriateand a relational data source and another table Identify the advantages of modelingManage Framework Manager Packages Specify Determinants metadata as a star schemaControl model versioning Create the Presentation View Create virtual facts to simplify writingNest packages Identify conformed vs. non-conformed queries

dimensions Use calculations to createCreate star schema groupings to provide commonly-needed query items for authors

line authors with logical groupings of query Make time-based queries simple to authorDiscuss IBM Cognos and Performance subjects by implementing a time dimensionManagement Work with Different Query Subject Types Use determinants to specify multiple levelsExamine the characteristics of operational Identify the effects on generated SQL of granularity and prevent double-countingdatabases and databases designed for when modifying query subjects, SQL Identify the dimensions associated with areporting settings and relationships fact tableExamine key modeling recommendations Set Security in Framework Manager Identify key differences andExamine the IBM Cognos BI and Framework Restrict access to packages recommendations for using data source,Manager workflow processes Create and apply security filters model, and stored procedure queryVerify relationships and query item Restrict access to objects in the model subjectsproperties Create Analysis Objects Examine the IBM Cognos BI securityDescribe multi-fact queries and when full Sort members for presentation and environmentouter joins are appropriate predictability Apply dimensional information to relationalIdentify the advantages of modeling Manage MUNs in Framework Manager Metadata to enable OLAP-style queriesmetadata as a star schema Define members and member unique Describe model types and data entitiesCreate virtual facts to simplify writing queries names Identify conformed values between dataUse calculations to create Identify changes that impact a MUN sourcescommonly-needed query items for authors Model for Drill Through in Framework Governors that affect SQL generation


Make time-based queries simple to author Manager Identify session and model parametersby implementing a time dimension Define a report drill through Perform basic maintenance andUse determinants to specify multiple levels Define a package-based drill through management on a modelof granularity and prevent double-counting Identify drill-through values Identify and implement techniques toIdentify the dimensions associated with a Advanced Generated SQL Concepts and optimize and tune your Frameworkfact table Complex Queries Manager modelsIdentify key differences and Stitch query SQL Implement repository controlrecommendations for using data source, Conformed and non-conformed Connect to an OLAP data source (cube) inmodel, and stored procedure query subjects dimensions in generated SQL a Framework Manager projectExamine the IBM Cognos BI security Multi-fact/multi-grain stitch query SQL Specify package languages and functionenvironment Variances in Report Studio generated setsApply dimensional information to relational SQLMetadata to enable OLAP-style queries Dimensionally modeled relational SQLDescribe model types and data entities generation lineIdentify conformed values between data Cross join SQL Describe IBM Cognos componentssources Various results sets for multi-fact queries Describe IBM Cognos architecture at aGovernors that affect SQL generation Use Advanced Parameterization high levelIdentify session and model parameters Techniques in Framework Manger Define IBM Cognos groups and rolesPerform basic maintenance and Leverage session, model, and custom Explain how to extend IBM Cognosmanagement on a model parameters Identify Common Data StructuresIdentify and implement techniques to Create prompt macros Examine relationships and cardinalityoptimize and tune your Framework Manager Leverage macro functions associated Identify different data trapsmodels with security Examine OLAP data sourcesImplement repository control Model Maintenance and Extensibility Gather RequirementsConnect to an OLAP data source (cube) in a Remap metadata to another source Define reporting requirementsFramework Manager project Import and link a second data source Explore data sources to identify dataSpecify package languages and function Run scripts to automate or update a access strategiessets model Create a Baseline Project

View lineage Define a project and its structureCreate a model report Describe the Framework Manager

line Optimize and Tune Framework Manager environmentDescribe IBM Cognos components Models Create a baseline projectDescribe IBM Cognos architecture at a high Work in a Multi-Modeler Environment Enhance the model with additionallevel Segment and link a project metadataDefine IBM Cognos groups and roles Branch a project and merge results Prepare Reusable MetadataExplain how to extend IBM Cognos Manage OLAP Data Sources Ensure efficient filters by configuringIdentify Common Data Structures Publish an OLAP model prompt propertiesExamine relationships and cardinality Publish a model with multiple OLAP data Model for Predictable Results: IdentifyIdentify different data traps sources Reporting IssuesExamine OLAP data sources Publish a model with an OLAP data Describe how IBM Cognos BI usesGather Requirements source and a relational data source cardinalityDefine reporting requirements Manage Framework Manager Packages Identify reporting trapsExplore data sources to identify data access Control model versioning Use tools to analyze the modelstrategies Nest packages Model for Predictable Results: Virtual StarCreate a Baseline Project SchemasDefine a project and its structure Model in layersDescribe the Framework Manager line Create aliases to avoid ambiguous joinsenvironment Discuss IBM Cognos and Performance Merge query subjects to create as viewCreate a baseline project Management behaviorEnhance the model with additional metadata Examine the characteristics of Model for Predictable Results: ConsolidatePrepare Reusable Metadata operational databases and databases MetadataEnsure efficient filters by configuring prompt designed for reporting Create virtual dimensions to resolveproperties Examine key modeling recommendations fact-to-fact joinsModel for Predictable Results: Identify Examine the IBM Cognos BI and Create a consolidated modeling layer forReporting Issues Framework Manager workflow processes presentation purposesDescribe how IBM Cognos BI uses Verify relationships and query item Consolidate snowflake dimensions withcardinality properties model query subjectsIdentify reporting traps Describe multi-fact queries and when full Simplify facts by hiding unnecessary codesUse tools to analyze the model outer joins are appropriate Calculations and FiltersModel for Predictable Results: Virtual Star Identify the advantages of modeling Use static filters to reduce the dataSchemas metadata as a star schema returnedModel in layers Create virtual facts to simplify writing Use macros and parameters inCreate aliases to avoid ambiguous joins queries calculations and filters to dynamicallyMerge query subjects to create as view Use calculations to create control the data returnedbehavior commonly-needed query items for Implement a Time DimensionModel for Predictable Results: Consolidate authors Resolve confusion caused by multiple


Metadata Make time-based queries simple to relationships between a time dimensionCreate virtual dimensions to resolve author by implementing a time dimension and another tablefact-to-fact joins Use determinants to specify multiple Specify DeterminantsCreate a consolidated modeling layer for levels of granularity and prevent Create the Presentation Viewpresentation purposes double-counting Identify conformed vs. non-conformedConsolidate snowflake dimensions with Identify the dimensions associated with a dimensionsmodel query subjects fact table Create star schema groupings to provideSimplify facts by hiding unnecessary codes Identify key differences and authors with logical groupings of queryCalculations and Filters recommendations for using data source, subjectsUse static filters to reduce the data returned model, and stored procedure query Work with Different Query Subject TypesUse macros and parameters in calculations subjects Identify the effects on generated SQLand filters to dynamically control the data Examine the IBM Cognos BI security when modifying query subjects, SQLreturned environment settings and relationshipsImplement a Time Dimension Apply dimensional information to Set Security in Framework ManagerResolve confusion caused by multiple relational Metadata to enable OLAP-style Restrict access to packagesrelationships between a time dimension and queries Create and apply security filtersanother table Describe model types and data entities Restrict access to objects in the modelSpecify Determinants Identify conformed values between data Create Analysis ObjectsCreate the Presentation View sources Sort members for presentation andIdentify conformed vs. non-conformed Governors that affect SQL generation predictabilitydimensions Identify session and model parameters Manage MUNs in Framework ManagerCreate star schema groupings to provide Perform basic maintenance and Define members and member uniqueauthors with logical groupings of query management on a model namessubjects Identify and implement techniques to Identify changes that impact a MUNWork with Different Query Subject Types optimize and tune your Framework Model for Drill Through in FrameworkIdentify the effects on generated SQL when Manager models Managermodifying query subjects, SQL settings and Implement repository control Define a report drill throughrelationships Connect to an OLAP data source (cube) Define a package-based drill throughSet Security in Framework Manager in a Framework Manager project Identify drill-through valuesRestrict access to packages Specify package languages and function Advanced Generated SQL Concepts andCreate and apply security filters sets Complex QueriesRestrict access to objects in the model Stitch query SQLCreate Analysis Objects Conformed and non-conformedSort members for presentation and line dimensions in generated SQLpredictability Describe IBM Cognos components Multi-fact/multi-grain stitch query SQLManage MUNs in Framework Manager Describe IBM Cognos architecture at a Variances in Report Studio generated SQLDefine members and member unique names high level Dimensionally modeled relational SQLIdentify changes that impact a MUN Define IBM Cognos groups and roles generationModel for Drill Through in Framework Explain how to extend IBM Cognos Cross join SQLManager Identify Common Data Structures Various results sets for multi-fact queriesDefine a report drill through Examine relationships and cardinality Use Advanced ParameterizationDefine a package-based drill through Identify different data traps Techniques in Framework MangerIdentify drill-through values Examine OLAP data sources Leverage session, model, and customAdvanced Generated SQL Concepts and Gather Requirements parametersComplex Queries Define reporting requirements Create prompt macrosStitch query SQL Explore data sources to identify data Leverage macro functions associated withConformed and non-conformed dimensions access strategies securityin generated SQL Create a Baseline Project Model Maintenance and ExtensibilityMulti-fact/multi-grain stitch query SQL Define a project and its structure Remap metadata to another sourceVariances in Report Studio generated SQL Describe the Framework Manager Import and link a second data sourceDimensionally modeled relational SQL environment Run scripts to automate or update a modelgeneration Create a baseline project View lineageCross join SQL Enhance the model with additional Create a model reportVarious results sets for multi-fact queries metadata Optimize and Tune Framework ManagerUse Advanced Parameterization Techniques Prepare Reusable Metadata Modelsin Framework Manger Ensure efficient filters by configuring Work in a Multi-Modeler EnvironmentLeverage session, model, and custom prompt properties Segment and link a projectparameters Model for Predictable Results: Identify Branch a project and merge resultsCreate prompt macros Reporting Issues Manage OLAP Data SourcesLeverage macro functions associated with Describe how IBM Cognos BI uses Publish an OLAP modelsecurity cardinality Publish a model with multiple OLAP dataModel Maintenance and Extensibility Identify reporting traps sourcesRemap metadata to another source Use tools to analyze the model Publish a model with an OLAP data sourceImport and link a second data source Model for Predictable Results: Virtual and a relational data sourceRun scripts to automate or update a model Star Schemas Manage Framework Manager PackagesView lineage Model in layers Control model versioning


Create a model report Create aliases to avoid ambiguous joins Nest packagesOptimize and Tune Framework Manager Merge query subjects to create as viewModels behaviorWork in a Multi-Modeler Environment Model for Predictable Results: lineSegment and link a project Consolidate Metadata Describe IBM Cognos componentsBranch a project and merge results Create virtual dimensions to resolve Describe IBM Cognos architecture at aManage OLAP Data Sources fact-to-fact joins high levelPublish an OLAP model Create a consolidated modeling layer for Define IBM Cognos groups and rolesPublish a model with multiple OLAP data presentation purposes Explain how to extend IBM Cognossources Consolidate snowflake dimensions with Identify Common Data StructuresPublish a model with an OLAP data source model query subjects Examine relationships and cardinalityand a relational data source Simplify facts by hiding unnecessary Identify different data trapsManage Framework Manager Packages codes Examine OLAP data sourcesControl model versioning Calculations and Filters Gather RequirementsNest packages Use static filters to reduce the data Define reporting requirements

returned Explore data sources to identify dataUse macros and parameters in access strategies

line calculations and filters to dynamically Create a Baseline ProjectDescribe IBM Cognos components control the data returned Define a project and its structureDescribe IBM Cognos architecture at a high Implement a Time Dimension Describe the Framework Managerlevel Resolve confusion caused by multiple environmentDefine IBM Cognos groups and roles relationships between a time dimension Create a baseline projectExplain how to extend IBM Cognos and another table Enhance the model with additionalIdentify Common Data Structures Specify Determinants metadataExamine relationships and cardinality Create the Presentation View Prepare Reusable MetadataIdentify different data traps Identify conformed vs. non-conformed Ensure efficient filters by configuringExamine OLAP data sources dimensions prompt propertiesGather Requirements Create star schema groupings to provide Model for Predictable Results: IdentifyDefine reporting requirements authors with logical groupings of query Reporting IssuesExplore data sources to identify data access subjects Describe how IBM Cognos BI usesstrategies Work with Different Query Subject Types cardinalityCreate a Baseline Project Identify the effects on generated SQL Identify reporting trapsDefine a project and its structure when modifying query subjects, SQL Use tools to analyze the modelDescribe the Framework Manager settings and relationships Model for Predictable Results: Virtual Starenvironment Set Security in Framework Manager SchemasCreate a baseline project Restrict access to packages Model in layersEnhance the model with additional metadata Create and apply security filters Create aliases to avoid ambiguous joinsPrepare Reusable Metadata Restrict access to objects in the model Merge query subjects to create as viewEnsure efficient filters by configuring prompt Create Analysis Objects behaviorproperties Sort members for presentation and Model for Predictable Results: ConsolidateModel for Predictable Results: Identify predictability MetadataReporting Issues Manage MUNs in Framework Manager Create virtual dimensions to resolveDescribe how IBM Cognos BI uses Define members and member unique fact-to-fact joinscardinality names Create a consolidated modeling layer forIdentify reporting traps Identify changes that impact a MUN presentation purposesUse tools to analyze the model Model for Drill Through in Framework Consolidate snowflake dimensions withModel for Predictable Results: Virtual Star Manager model query subjectsSchemas Define a report drill through Simplify facts by hiding unnecessary codesModel in layers Define a package-based drill through Calculations and FiltersCreate aliases to avoid ambiguous joins Identify drill-through values Use static filters to reduce the dataMerge query subjects to create as view Advanced Generated SQL Concepts and returnedbehavior Complex Queries Use macros and parameters inModel for Predictable Results: Consolidate Stitch query SQL calculations and filters to dynamicallyMetadata Conformed and non-conformed control the data returnedCreate virtual dimensions to resolve dimensions in generated SQL Implement a Time Dimensionfact-to-fact joins Multi-fact/multi-grain stitch query SQL Resolve confusion caused by multipleCreate a consolidated modeling layer for Variances in Report Studio generated relationships between a time dimensionpresentation purposes SQL and another tableConsolidate snowflake dimensions with Dimensionally modeled relational SQL Specify Determinantsmodel query subjects generation Create the Presentation ViewSimplify facts by hiding unnecessary codes Cross join SQL Identify conformed vs. non-conformedCalculations and Filters Various results sets for multi-fact queries dimensionsUse static filters to reduce the data returned Use Advanced Parameterization Create star schema groupings to provideUse macros and parameters in calculations Techniques in Framework Manger authors with logical groupings of queryand filters to dynamically control the data Leverage session, model, and custom subjectsreturned parameters Work with Different Query Subject Types


Implement a Time Dimension Create prompt macros Identify the effects on generated SQLResolve confusion caused by multiple Leverage macro functions associated when modifying query subjects, SQLrelationships between a time dimension and with security settings and relationshipsanother table Model Maintenance and Extensibility Set Security in Framework ManagerSpecify Determinants Remap metadata to another source Restrict access to packagesCreate the Presentation View Import and link a second data source Create and apply security filtersIdentify conformed vs. non-conformed Run scripts to automate or update a Restrict access to objects in the modeldimensions model Create Analysis ObjectsCreate star schema groupings to provide View lineage Sort members for presentation andauthors with logical groupings of query Create a model report predictabilitysubjects Optimize and Tune Framework Manager Manage MUNs in Framework ManagerWork with Different Query Subject Types Models Define members and member uniqueIdentify the effects on generated SQL when Work in a Multi-Modeler Environment namesmodifying query subjects, SQL settings and Segment and link a project Identify changes that impact a MUNrelationships Branch a project and merge results Model for Drill Through in FrameworkSet Security in Framework Manager Manage OLAP Data Sources ManagerRestrict access to packages Publish an OLAP model Define a report drill throughCreate and apply security filters Publish a model with multiple OLAP data Define a package-based drill throughRestrict access to objects in the model sources Identify drill-through valuesCreate Analysis Objects Publish a model with an OLAP data Advanced Generated SQL Concepts andSort members for presentation and source and a relational data source Complex Queriespredictability Manage Framework Manager Packages Stitch query SQLManage MUNs in Framework Manager Control model versioning Conformed and non-conformedDefine members and member unique names Nest packages dimensions in generated SQLIdentify changes that impact a MUN Multi-fact/multi-grain stitch query SQLModel for Drill Through in Framework Variances in Report Studio generated SQLManager line Dimensionally modeled relational SQLDefine a report drill through Discuss IBM Cognos and Performance generationDefine a package-based drill through Management Cross join SQLIdentify drill-through values Examine the characteristics of Various results sets for multi-fact queriesAdvanced Generated SQL Concepts and operational databases and databases Use Advanced ParameterizationComplex Queries designed for reporting Techniques in Framework MangerStitch query SQL Examine key modeling recommendations Leverage session, model, and customConformed and non-conformed dimensions Examine the IBM Cognos BI and parametersin generated SQL Framework Manager workflow processes Create prompt macrosMulti-fact/multi-grain stitch query SQL Verify relationships and query item Leverage macro functions associated withVariances in Report Studio generated SQL properties securityDimensionally modeled relational SQL Describe multi-fact queries and when full Model Maintenance and Extensibilitygeneration outer joins are appropriate Remap metadata to another sourceCross join SQL Identify the advantages of modeling Import and link a second data sourceVarious results sets for multi-fact queries metadata as a star schema Run scripts to automate or update a modelUse Advanced Parameterization Techniques Create virtual facts to simplify writing View lineagein Framework Manger queries Create a model reportLeverage session, model, and custom Use calculations to create Optimize and Tune Framework Managerparameters commonly-needed query items for ModelsCreate prompt macros authors Work in a Multi-Modeler EnvironmentLeverage macro functions associated with Make time-based queries simple to Segment and link a projectsecurity author by implementing a time dimension Branch a project and merge resultsModel Maintenance and Extensibility Use determinants to specify multiple Manage OLAP Data SourcesRemap metadata to another source levels of granularity and prevent Publish an OLAP modelImport and link a second data source double-counting Publish a model with multiple OLAP dataRun scripts to automate or update a model Identify the dimensions associated with a sourcesView lineage fact table Publish a model with an OLAP data sourceCreate a model report Identify key differences and and a relational data sourceOptimize and Tune Framework Manager recommendations for using data source, Manage Framework Manager PackagesModels model, and stored procedure query Control model versioningWork in a Multi-Modeler Environment subjects Nest packagesSegment and link a project Examine the IBM Cognos BI securityBranch a project and merge results environmentManage OLAP Data Sources Apply dimensional information to linePublish an OLAP model relational Metadata to enable OLAP-style Describe IBM Cognos componentsPublish a model with multiple OLAP data queries Describe IBM Cognos architecture at asources Describe model types and data entities high levelPublish a model with an OLAP data source Identify conformed values between data Define IBM Cognos groups and rolesand a relational data source sources Explain how to extend IBM CognosManage Framework Manager Packages Governors that affect SQL generation Identify Common Data Structures


Control model versioning Identify session and model parameters Examine relationships and cardinalityNest packages Perform basic maintenance and Identify different data traps

management on a model Examine OLAP data sourcesIdentify and implement techniques to Gather Requirements

line optimize and tune your Framework Define reporting requirementsDescribe IBM Cognos components Manager models Explore data sources to identify dataDescribe IBM Cognos architecture at a high Implement repository control access strategieslevel Connect to an OLAP data source (cube) Create a Baseline ProjectDefine IBM Cognos groups and roles in a Framework Manager project Define a project and its structureExplain how to extend IBM Cognos Specify package languages and function Describe the Framework ManagerIdentify Common Data Structures sets environmentExamine relationships and cardinality Create a baseline projectIdentify different data traps Enhance the model with additionalExamine OLAP data sources line metadataGather Requirements Describe IBM Cognos components Prepare Reusable MetadataDefine reporting requirements Describe IBM Cognos architecture at a Ensure efficient filters by configuringExplore data sources to identify data access high level prompt propertiesstrategies Define IBM Cognos groups and roles Model for Predictable Results: IdentifyCreate a Baseline Project Explain how to extend IBM Cognos Reporting IssuesDefine a project and its structure Identify Common Data Structures Describe how IBM Cognos BI usesDescribe the Framework Manager Examine relationships and cardinality cardinalityenvironment Identify different data traps Identify reporting trapsCreate a baseline project Examine OLAP data sources Use tools to analyze the modelEnhance the model with additional metadata Gather Requirements Model for Predictable Results: Virtual StarPrepare Reusable Metadata Define reporting requirements SchemasEnsure efficient filters by configuring prompt Explore data sources to identify data Model in layersproperties access strategies Create aliases to avoid ambiguous joinsModel for Predictable Results: Identify Create a Baseline Project Merge query subjects to create as viewReporting Issues Define a project and its structure behaviorDescribe how IBM Cognos BI uses Describe the Framework Manager Model for Predictable Results: Consolidatecardinality environment MetadataIdentify reporting traps Create a baseline project Create virtual dimensions to resolveUse tools to analyze the model Enhance the model with additional fact-to-fact joinsModel for Predictable Results: Virtual Star metadata Create a consolidated modeling layer forSchemas Prepare Reusable Metadata presentation purposesModel in layers Ensure efficient filters by configuring Consolidate snowflake dimensions withCreate aliases to avoid ambiguous joins prompt properties model query subjectsMerge query subjects to create as view Model for Predictable Results: Identify Simplify facts by hiding unnecessary codesbehavior Reporting Issues Calculations and FiltersModel for Predictable Results: Consolidate Describe how IBM Cognos BI uses Use static filters to reduce the dataMetadata cardinality returnedCreate virtual dimensions to resolve Identify reporting traps Use macros and parameters infact-to-fact joins Use tools to analyze the model calculations and filters to dynamicallyCreate a consolidated modeling layer for Model for Predictable Results: Virtual control the data returnedpresentation purposes Star Schemas Implement a Time DimensionConsolidate snowflake dimensions with Model in layers Resolve confusion caused by multiplemodel query subjects Create aliases to avoid ambiguous joins relationships between a time dimensionSimplify facts by hiding unnecessary codes Merge query subjects to create as view and another tableCalculations and Filters behavior Specify DeterminantsUse static filters to reduce the data returned Model for Predictable Results: Create the Presentation ViewUse macros and parameters in calculations Consolidate Metadata Identify conformed vs. non-conformedand filters to dynamically control the data Create virtual dimensions to resolve dimensionsreturned fact-to-fact joins Create star schema groupings to provideImplement a Time Dimension Create a consolidated modeling layer for authors with logical groupings of queryResolve confusion caused by multiple presentation purposes subjectsrelationships between a time dimension and Consolidate snowflake dimensions with Work with Different Query Subject Typesanother table model query subjects Identify the effects on generated SQLSpecify Determinants Simplify facts by hiding unnecessary when modifying query subjects, SQLCreate the Presentation View codes settings and relationshipsIdentify conformed vs. non-conformed Calculations and Filters Set Security in Framework Managerdimensions Use static filters to reduce the data Restrict access to packagesCreate star schema groupings to provide returned Create and apply security filtersauthors with logical groupings of query Use macros and parameters in Restrict access to objects in the modelsubjects calculations and filters to dynamically Create Analysis ObjectsWork with Different Query Subject Types control the data returned Sort members for presentation andIdentify the effects on generated SQL when Implement a Time Dimension predictability


modifying query subjects, SQL settings and Resolve confusion caused by multiple Manage MUNs in Framework Managerrelationships relationships between a time dimension Define members and member uniqueSet Security in Framework Manager and another table namesRestrict access to packages Specify Determinants Identify changes that impact a MUNCreate and apply security filters Create the Presentation View Model for Drill Through in FrameworkRestrict access to objects in the model Identify conformed vs. non-conformed ManagerCreate Analysis Objects dimensions Define a report drill throughSort members for presentation and Create star schema groupings to provide Define a package-based drill throughpredictability authors with logical groupings of query Identify drill-through valuesManage MUNs in Framework Manager subjects Advanced Generated SQL Concepts andDefine members and member unique names Work with Different Query Subject Types Complex QueriesIdentify changes that impact a MUN Identify the effects on generated SQL Stitch query SQLModel for Drill Through in Framework when modifying query subjects, SQL Conformed and non-conformedManager settings and relationships dimensions in generated SQLDefine a report drill through Set Security in Framework Manager Multi-fact/multi-grain stitch query SQLDefine a package-based drill through Restrict access to packages Variances in Report Studio generated SQLIdentify drill-through values Create and apply security filters Dimensionally modeled relational SQLAdvanced Generated SQL Concepts and Restrict access to objects in the model generationComplex Queries Create Analysis Objects Cross join SQLStitch query SQL Sort members for presentation and Various results sets for multi-fact queriesConformed and non-conformed dimensions predictability Use Advanced Parameterizationin generated SQL Manage MUNs in Framework Manager Techniques in Framework MangerMulti-fact/multi-grain stitch query SQL Define members and member unique Leverage session, model, and customVariances in Report Studio generated SQL names parametersDimensionally modeled relational SQL Identify changes that impact a MUN Create prompt macrosgeneration Model for Drill Through in Framework Leverage macro functions associated withCross join SQL Manager securityVarious results sets for multi-fact queries Define a report drill through Model Maintenance and ExtensibilityUse Advanced Parameterization Techniques Define a package-based drill through Remap metadata to another sourcein Framework Manger Identify drill-through values Import and link a second data sourceLeverage session, model, and custom Advanced Generated SQL Concepts and Run scripts to automate or update a modelparameters Complex Queries View lineageCreate prompt macros Stitch query SQL Create a model reportLeverage macro functions associated with Conformed and non-conformed Optimize and Tune Framework Managersecurity dimensions in generated SQL ModelsModel Maintenance and Extensibility Multi-fact/multi-grain stitch query SQL Work in a Multi-Modeler EnvironmentRemap metadata to another source Variances in Report Studio generated Segment and link a projectImport and link a second data source SQL Branch a project and merge resultsRun scripts to automate or update a model Dimensionally modeled relational SQL Manage OLAP Data SourcesView lineage generation Publish an OLAP modelCreate a model report Cross join SQL Publish a model with multiple OLAP dataOptimize and Tune Framework Manager Various results sets for multi-fact queries sourcesModels Use Advanced Parameterization Publish a model with an OLAP data sourceWork in a Multi-Modeler Environment Techniques in Framework Manger and a relational data sourceSegment and link a project Leverage session, model, and custom Manage Framework Manager PackagesBranch a project and merge results parameters Control model versioningManage OLAP Data Sources Create prompt macros Nest packagesPublish an OLAP model Leverage macro functions associatedPublish a model with multiple OLAP data with securitysources Model Maintenance and Extensibility linePublish a model with an OLAP data source Remap metadata to another source Describe IBM Cognos componentsand a relational data source Import and link a second data source Describe IBM Cognos architecture at aManage Framework Manager Packages Run scripts to automate or update a high levelControl model versioning model Define IBM Cognos groups and rolesNest packages View lineage Explain how to extend IBM Cognos

Create a model report Identify Common Data StructuresOptimize and Tune Framework Manager Examine relationships and cardinality

line Models Identify different data trapsDiscuss IBM Cognos and Performance Work in a Multi-Modeler Environment Examine OLAP data sourcesManagement Segment and link a project Gather RequirementsExamine the characteristics of operational Branch a project and merge results Define reporting requirementsdatabases and databases designed for Manage OLAP Data Sources Explore data sources to identify datareporting Publish an OLAP model access strategiesExamine key modeling recommendations Publish a model with multiple OLAP data Create a Baseline ProjectExamine the IBM Cognos BI and Framework sources Define a project and its structureManager workflow processes Publish a model with an OLAP data Describe the Framework Manager


Verify relationships and query item source and a relational data source environmentproperties Manage Framework Manager Packages Create a baseline projectDescribe multi-fact queries and when full Control model versioning Enhance the model with additionalouter joins are appropriate Nest packages metadataIdentify the advantages of modeling Prepare Reusable Metadatametadata as a star schema Ensure efficient filters by configuringCreate virtual facts to simplify writing queries line prompt propertiesUse calculations to create Describe IBM Cognos components Model for Predictable Results: Identifycommonly-needed query items for authors Describe IBM Cognos architecture at a Reporting IssuesMake time-based queries simple to author high level Describe how IBM Cognos BI usesby implementing a time dimension Define IBM Cognos groups and roles cardinalityUse determinants to specify multiple levels Explain how to extend IBM Cognos Identify reporting trapsof granularity and prevent double-counting Identify Common Data Structures Use tools to analyze the modelIdentify the dimensions associated with a Examine relationships and cardinality Model for Predictable Results: Virtual Starfact table Identify different data traps SchemasIdentify key differences and Examine OLAP data sources Model in layersrecommendations for using data source, Gather Requirements Create aliases to avoid ambiguous joinsmodel, and stored procedure query subjects Define reporting requirements Merge query subjects to create as viewExamine the IBM Cognos BI security Explore data sources to identify data behaviorenvironment access strategies Model for Predictable Results: ConsolidateApply dimensional information to relational Create a Baseline Project MetadataMetadata to enable OLAP-style queries Define a project and its structure Create virtual dimensions to resolveDescribe model types and data entities Describe the Framework Manager fact-to-fact joinsIdentify conformed values between data environment Create a consolidated modeling layer forsources Create a baseline project presentation purposesGovernors that affect SQL generation Enhance the model with additional Consolidate snowflake dimensions withIdentify session and model parameters metadata model query subjectsPerform basic maintenance and Prepare Reusable Metadata Simplify facts by hiding unnecessary codesmanagement on a model Ensure efficient filters by configuring Calculations and FiltersIdentify and implement techniques to prompt properties Use static filters to reduce the dataoptimize and tune your Framework Manager Model for Predictable Results: Identify returnedmodels Reporting Issues Use macros and parameters inImplement repository control Describe how IBM Cognos BI uses calculations and filters to dynamicallyConnect to an OLAP data source (cube) in a cardinality control the data returnedFramework Manager project Identify reporting traps Implement a Time DimensionSpecify package languages and function Use tools to analyze the model Resolve confusion caused by multiplesets Model for Predictable Results: Virtual relationships between a time dimension

Star Schemas and another tableModel in layers Specify Determinants

line Create aliases to avoid ambiguous joins Create the Presentation ViewDescribe IBM Cognos components Merge query subjects to create as view Identify conformed vs. non-conformedDescribe IBM Cognos architecture at a high behavior dimensionslevel Model for Predictable Results: Create star schema groupings to provideDefine IBM Cognos groups and roles Consolidate Metadata authors with logical groupings of queryExplain how to extend IBM Cognos Create virtual dimensions to resolve subjectsIdentify Common Data Structures fact-to-fact joins Work with Different Query Subject TypesExamine relationships and cardinality Create a consolidated modeling layer for Identify the effects on generated SQLIdentify different data traps presentation purposes when modifying query subjects, SQLExamine OLAP data sources Consolidate snowflake dimensions with settings and relationshipsGather Requirements model query subjects Set Security in Framework ManagerDefine reporting requirements Simplify facts by hiding unnecessary Restrict access to packagesExplore data sources to identify data access codes Create and apply security filtersstrategies Calculations and Filters Restrict access to objects in the modelCreate a Baseline Project Use static filters to reduce the data Create Analysis ObjectsDefine a project and its structure returned Sort members for presentation andDescribe the Framework Manager Use macros and parameters in predictabilityenvironment calculations and filters to dynamically Manage MUNs in Framework ManagerCreate a baseline project control the data returned Define members and member uniqueEnhance the model with additional metadata Implement a Time Dimension namesPrepare Reusable Metadata Resolve confusion caused by multiple Identify changes that impact a MUNEnsure efficient filters by configuring prompt relationships between a time dimension Model for Drill Through in Frameworkproperties and another table ManagerModel for Predictable Results: Identify Specify Determinants Define a report drill throughReporting Issues Create the Presentation View Define a package-based drill throughDescribe how IBM Cognos BI uses Identify conformed vs. non-conformed Identify drill-through valuescardinality dimensions Advanced Generated SQL Concepts and


Identify reporting traps Create star schema groupings to provide Complex QueriesUse tools to analyze the model authors with logical groupings of query Stitch query SQLModel for Predictable Results: Virtual Star subjects Conformed and non-conformedSchemas Work with Different Query Subject Types dimensions in generated SQLModel in layers Identify the effects on generated SQL Multi-fact/multi-grain stitch query SQLCreate aliases to avoid ambiguous joins when modifying query subjects, SQL Variances in Report Studio generated SQLMerge query subjects to create as view settings and relationships Dimensionally modeled relational SQLbehavior Set Security in Framework Manager generationModel for Predictable Results: Consolidate Restrict access to packages Cross join SQLMetadata Create and apply security filters Various results sets for multi-fact queriesCreate virtual dimensions to resolve Restrict access to objects in the model Use Advanced Parameterizationfact-to-fact joins Create Analysis Objects Techniques in Framework MangerCreate a consolidated modeling layer for Sort members for presentation and Leverage session, model, and custompresentation purposes predictability parametersConsolidate snowflake dimensions with Manage MUNs in Framework Manager Create prompt macrosmodel query subjects Define members and member unique Leverage macro functions associated withSimplify facts by hiding unnecessary codes names securityCalculations and Filters Identify changes that impact a MUN Model Maintenance and ExtensibilityUse static filters to reduce the data returned Model for Drill Through in Framework Remap metadata to another sourceUse macros and parameters in calculations Manager Import and link a second data sourceand filters to dynamically control the data Define a report drill through Run scripts to automate or update a modelreturned Define a package-based drill through View lineageImplement a Time Dimension Identify drill-through values Create a model reportResolve confusion caused by multiple Advanced Generated SQL Concepts and Optimize and Tune Framework Managerrelationships between a time dimension and Complex Queries Modelsanother table Stitch query SQL Work in a Multi-Modeler EnvironmentSpecify Determinants Conformed and non-conformed Segment and link a projectCreate the Presentation View dimensions in generated SQL Branch a project and merge resultsIdentify conformed vs. non-conformed Multi-fact/multi-grain stitch query SQL Manage OLAP Data Sourcesdimensions Variances in Report Studio generated Publish an OLAP modelCreate star schema groupings to provide SQL Publish a model with multiple OLAP dataauthors with logical groupings of query Dimensionally modeled relational SQL sourcessubjects generation Publish a model with an OLAP data sourceWork with Different Query Subject Types Cross join SQL and a relational data sourceIdentify the effects on generated SQL when Various results sets for multi-fact queries Manage Framework Manager Packagesmodifying query subjects, SQL settings and Use Advanced Parameterization Control model versioningrelationships Techniques in Framework Manger Nest packagesSet Security in Framework Manager Leverage session, model, and customRestrict access to packages parametersCreate and apply security filters Create prompt macros lineRestrict access to objects in the model Leverage macro functions associated Discuss IBM Cognos and PerformanceCreate Analysis Objects with security ManagementSort members for presentation and Model Maintenance and Extensibility Examine the characteristics of operationalpredictability Remap metadata to another source databases and databases designed forManage MUNs in Framework Manager Import and link a second data source reportingDefine members and member unique names Run scripts to automate or update a Examine key modeling recommendationsIdentify changes that impact a MUN model Examine the IBM Cognos BI andModel for Drill Through in Framework View lineage Framework Manager workflow processesManager Create a model report Verify relationships and query itemDefine a report drill through Optimize and Tune Framework Manager propertiesDefine a package-based drill through Models Describe multi-fact queries and when fullIdentify drill-through values Work in a Multi-Modeler Environment outer joins are appropriateAdvanced Generated SQL Concepts and Segment and link a project Identify the advantages of modelingComplex Queries Branch a project and merge results metadata as a star schemaStitch query SQL Manage OLAP Data Sources Create virtual facts to simplify writingConformed and non-conformed dimensions Publish an OLAP model queriesin generated SQL Publish a model with multiple OLAP data Use calculations to createMulti-fact/multi-grain stitch query SQL sources commonly-needed query items for authorsVariances in Report Studio generated SQL Publish a model with an OLAP data Make time-based queries simple to authorDimensionally modeled relational SQL source and a relational data source by implementing a time dimensiongeneration Manage Framework Manager Packages Use determinants to specify multiple levelsCross join SQL Control model versioning of granularity and prevent double-countingVarious results sets for multi-fact queries Nest packages Identify the dimensions associated with aUse Advanced Parameterization Techniques fact tablein Framework Manger Identify key differences andLeverage session, model, and custom line recommendations for using data source,


parameters Describe IBM Cognos components model, and stored procedure queryCreate prompt macros Describe IBM Cognos architecture at a subjectsLeverage macro functions associated with high level Examine the IBM Cognos BI securitysecurity Define IBM Cognos groups and roles environmentModel Maintenance and Extensibility Explain how to extend IBM Cognos Apply dimensional information to relationalRemap metadata to another source Identify Common Data Structures Metadata to enable OLAP-style queriesImport and link a second data source Examine relationships and cardinality Describe model types and data entitiesRun scripts to automate or update a model Identify different data traps Identify conformed values between dataView lineage Examine OLAP data sources sourcesCreate a model report Gather Requirements Governors that affect SQL generationOptimize and Tune Framework Manager Define reporting requirements Identify session and model parametersModels Explore data sources to identify data Perform basic maintenance andWork in a Multi-Modeler Environment access strategies management on a modelSegment and link a project Create a Baseline Project Identify and implement techniques toBranch a project and merge results Define a project and its structure optimize and tune your FrameworkManage OLAP Data Sources Describe the Framework Manager Manager modelsPublish an OLAP model environment Implement repository controlPublish a model with multiple OLAP data Create a baseline project Connect to an OLAP data source (cube) insources Enhance the model with additional a Framework Manager projectPublish a model with an OLAP data source metadata Specify package languages and functionand a relational data source Prepare Reusable Metadata setsManage Framework Manager Packages Ensure efficient filters by configuringControl model versioning prompt propertiesNest packages Model for Predictable Results: Identify line

Reporting Issues Describe IBM Cognos componentsDescribe how IBM Cognos BI uses Describe IBM Cognos architecture at a

line cardinality high levelDescribe IBM Cognos components Identify reporting traps Define IBM Cognos groups and rolesDescribe IBM Cognos architecture at a high Use tools to analyze the model Explain how to extend IBM Cognoslevel Model for Predictable Results: Virtual Identify Common Data StructuresDefine IBM Cognos groups and roles Star Schemas Examine relationships and cardinalityExplain how to extend IBM Cognos Model in layers Identify different data trapsIdentify Common Data Structures Create aliases to avoid ambiguous joins Examine OLAP data sourcesExamine relationships and cardinality Merge query subjects to create as view Gather RequirementsIdentify different data traps behavior Define reporting requirementsExamine OLAP data sources Model for Predictable Results: Explore data sources to identify dataGather Requirements Consolidate Metadata access strategiesDefine reporting requirements Create virtual dimensions to resolve Create a Baseline ProjectExplore data sources to identify data access fact-to-fact joins Define a project and its structurestrategies Create a consolidated modeling layer for Describe the Framework ManagerCreate a Baseline Project presentation purposes environmentDefine a project and its structure Consolidate snowflake dimensions with Create a baseline projectDescribe the Framework Manager model query subjects Enhance the model with additionalenvironment Simplify facts by hiding unnecessary metadataCreate a baseline project codes Prepare Reusable MetadataEnhance the model with additional metadata Calculations and Filters Ensure efficient filters by configuringPrepare Reusable Metadata Use static filters to reduce the data prompt propertiesEnsure efficient filters by configuring prompt returned Model for Predictable Results: Identifyproperties Use macros and parameters in Reporting IssuesModel for Predictable Results: Identify calculations and filters to dynamically Describe how IBM Cognos BI usesReporting Issues control the data returned cardinalityDescribe how IBM Cognos BI uses Implement a Time Dimension Identify reporting trapscardinality Resolve confusion caused by multiple Use tools to analyze the modelIdentify reporting traps relationships between a time dimension Model for Predictable Results: Virtual StarUse tools to analyze the model and another table SchemasModel for Predictable Results: Virtual Star Specify Determinants Model in layersSchemas Create the Presentation View Create aliases to avoid ambiguous joinsModel in layers Identify conformed vs. non-conformed Merge query subjects to create as viewCreate aliases to avoid ambiguous joins dimensions behaviorMerge query subjects to create as view Create star schema groupings to provide Model for Predictable Results: Consolidatebehavior authors with logical groupings of query MetadataModel for Predictable Results: Consolidate subjects Create virtual dimensions to resolveMetadata Work with Different Query Subject Types fact-to-fact joinsCreate virtual dimensions to resolve Identify the effects on generated SQL Create a consolidated modeling layer forfact-to-fact joins when modifying query subjects, SQL presentation purposesCreate a consolidated modeling layer for settings and relationships Consolidate snowflake dimensions with


presentation purposes Set Security in Framework Manager model query subjectsConsolidate snowflake dimensions with Restrict access to packages Simplify facts by hiding unnecessary codesmodel query subjects Create and apply security filters Calculations and FiltersSimplify facts by hiding unnecessary codes Restrict access to objects in the model Use static filters to reduce the dataCalculations and Filters Create Analysis Objects returnedUse static filters to reduce the data returned Sort members for presentation and Use macros and parameters inUse macros and parameters in calculations predictability calculations and filters to dynamicallyand filters to dynamically control the data Manage MUNs in Framework Manager control the data returnedreturned Define members and member unique Implement a Time DimensionImplement a Time Dimension names Resolve confusion caused by multipleResolve confusion caused by multiple Identify changes that impact a MUN relationships between a time dimensionrelationships between a time dimension and Model for Drill Through in Framework and another tableanother table Manager Specify DeterminantsSpecify Determinants Define a report drill through Create the Presentation ViewCreate the Presentation View Define a package-based drill through Identify conformed vs. non-conformedIdentify conformed vs. non-conformed Identify drill-through values dimensionsdimensions Advanced Generated SQL Concepts and Create star schema groupings to provideCreate star schema groupings to provide Complex Queries authors with logical groupings of queryauthors with logical groupings of query Stitch query SQL subjectssubjects Conformed and non-conformed Work with Different Query Subject TypesWork with Different Query Subject Types dimensions in generated SQL Identify the effects on generated SQLIdentify the effects on generated SQL when Multi-fact/multi-grain stitch query SQL when modifying query subjects, SQLmodifying query subjects, SQL settings and Variances in Report Studio generated settings and relationshipsrelationships SQL Set Security in Framework ManagerSet Security in Framework Manager Dimensionally modeled relational SQL Restrict access to packagesRestrict access to packages generation Create and apply security filtersCreate and apply security filters Cross join SQL Restrict access to objects in the modelRestrict access to objects in the model Various results sets for multi-fact queries Create Analysis ObjectsCreate Analysis Objects Use Advanced Parameterization Sort members for presentation andSort members for presentation and Techniques in Framework Manger predictabilitypredictability Leverage session, model, and custom Manage MUNs in Framework ManagerManage MUNs in Framework Manager parameters Define members and member uniqueDefine members and member unique names Create prompt macros namesIdentify changes that impact a MUN Leverage macro functions associated Identify changes that impact a MUNModel for Drill Through in Framework with security Model for Drill Through in FrameworkManager Model Maintenance and Extensibility ManagerDefine a report drill through Remap metadata to another source Define a report drill throughDefine a package-based drill through Import and link a second data source Define a package-based drill throughIdentify drill-through values Run scripts to automate or update a Identify drill-through valuesAdvanced Generated SQL Concepts and model Advanced Generated SQL Concepts andComplex Queries View lineage Complex QueriesStitch query SQL Create a model report Stitch query SQLConformed and non-conformed dimensions Optimize and Tune Framework Manager Conformed and non-conformedin generated SQL Models dimensions in generated SQLMulti-fact/multi-grain stitch query SQL Work in a Multi-Modeler Environment Multi-fact/multi-grain stitch query SQLVariances in Report Studio generated SQL Segment and link a project Variances in Report Studio generated SQLDimensionally modeled relational SQL Branch a project and merge results Dimensionally modeled relational SQLgeneration Manage OLAP Data Sources generationCross join SQL Publish an OLAP model Cross join SQLVarious results sets for multi-fact queries Publish a model with multiple OLAP data Various results sets for multi-fact queriesUse Advanced Parameterization Techniques sources Use Advanced Parameterizationin Framework Manger Publish a model with an OLAP data Techniques in Framework MangerLeverage session, model, and custom source and a relational data source Leverage session, model, and customparameters Manage Framework Manager Packages parametersCreate prompt macros Control model versioning Create prompt macrosLeverage macro functions associated with Nest packages Leverage macro functions associated withsecurity securityModel Maintenance and Extensibility Model Maintenance and ExtensibilityRemap metadata to another source line Remap metadata to another sourceImport and link a second data source Discuss IBM Cognos and Performance Import and link a second data sourceRun scripts to automate or update a model Management Run scripts to automate or update a modelView lineage Examine the characteristics of View lineageCreate a model report operational databases and databases Create a model reportOptimize and Tune Framework Manager designed for reporting Optimize and Tune Framework ManagerModels Examine key modeling recommendations ModelsWork in a Multi-Modeler Environment Examine the IBM Cognos BI and Work in a Multi-Modeler Environment


Segment and link a project Framework Manager workflow processes Segment and link a projectBranch a project and merge results Verify relationships and query item Branch a project and merge resultsManage OLAP Data Sources properties Manage OLAP Data SourcesPublish an OLAP model Describe multi-fact queries and when full Publish an OLAP modelPublish a model with multiple OLAP data outer joins are appropriate Publish a model with multiple OLAP datasources Identify the advantages of modeling sourcesPublish a model with an OLAP data source metadata as a star schema Publish a model with an OLAP data sourceand a relational data source Create virtual facts to simplify writing and a relational data sourceManage Framework Manager Packages queries Manage Framework Manager PackagesControl model versioning Use calculations to create Control model versioningNest packages commonly-needed query items for Nest packages

authorsMake time-based queries simple to

line author by implementing a time dimension lineDescribe IBM Cognos components Use determinants to specify multiple Describe IBM Cognos componentsDescribe IBM Cognos architecture at a high levels of granularity and prevent Describe IBM Cognos architecture at alevel double-counting high levelDefine IBM Cognos groups and roles Identify the dimensions associated with a Define IBM Cognos groups and rolesExplain how to extend IBM Cognos fact table Explain how to extend IBM CognosIdentify Common Data Structures Identify key differences and Identify Common Data StructuresExamine relationships and cardinality recommendations for using data source, Examine relationships and cardinalityIdentify different data traps model, and stored procedure query Identify different data trapsExamine OLAP data sources subjects Examine OLAP data sourcesGather Requirements Examine the IBM Cognos BI security Gather RequirementsDefine reporting requirements environment Define reporting requirementsExplore data sources to identify data access Apply dimensional information to Explore data sources to identify datastrategies relational Metadata to enable OLAP-style access strategiesCreate a Baseline Project queries Create a Baseline ProjectDefine a project and its structure Describe model types and data entities Define a project and its structureDescribe the Framework Manager Identify conformed values between data Describe the Framework Managerenvironment sources environmentCreate a baseline project Governors that affect SQL generation Create a baseline projectEnhance the model with additional metadata Identify session and model parameters Enhance the model with additionalPrepare Reusable Metadata Perform basic maintenance and metadataEnsure efficient filters by configuring prompt management on a model Prepare Reusable Metadataproperties Identify and implement techniques to Ensure efficient filters by configuringModel for Predictable Results: Identify optimize and tune your Framework prompt propertiesReporting Issues Manager models Model for Predictable Results: IdentifyDescribe how IBM Cognos BI uses Implement repository control Reporting Issuescardinality Connect to an OLAP data source (cube) Describe how IBM Cognos BI usesIdentify reporting traps in a Framework Manager project cardinalityUse tools to analyze the model Specify package languages and function Identify reporting trapsModel for Predictable Results: Virtual Star sets Use tools to analyze the modelSchemas Model for Predictable Results: Virtual StarModel in layers SchemasCreate aliases to avoid ambiguous joins line Model in layersMerge query subjects to create as view Describe IBM Cognos components Create aliases to avoid ambiguous joinsbehavior Describe IBM Cognos architecture at a Merge query subjects to create as viewModel for Predictable Results: Consolidate high level behaviorMetadata Define IBM Cognos groups and roles Model for Predictable Results: ConsolidateCreate virtual dimensions to resolve Explain how to extend IBM Cognos Metadatafact-to-fact joins Identify Common Data Structures Create virtual dimensions to resolveCreate a consolidated modeling layer for Examine relationships and cardinality fact-to-fact joinspresentation purposes Identify different data traps Create a consolidated modeling layer forConsolidate snowflake dimensions with Examine OLAP data sources presentation purposesmodel query subjects Gather Requirements Consolidate snowflake dimensions withSimplify facts by hiding unnecessary codes Define reporting requirements model query subjectsCalculations and Filters Explore data sources to identify data Simplify facts by hiding unnecessary codesUse static filters to reduce the data returned access strategies Calculations and FiltersUse macros and parameters in calculations Create a Baseline Project Use static filters to reduce the dataand filters to dynamically control the data Define a project and its structure returnedreturned Describe the Framework Manager Use macros and parameters inImplement a Time Dimension environment calculations and filters to dynamicallyResolve confusion caused by multiple Create a baseline project control the data returnedrelationships between a time dimension and Enhance the model with additional Implement a Time Dimensionanother table metadata Resolve confusion caused by multiple


Specify Determinants Prepare Reusable Metadata relationships between a time dimensionCreate the Presentation View Ensure efficient filters by configuring and another tableIdentify conformed vs. non-conformed prompt properties Specify Determinantsdimensions Model for Predictable Results: Identify Create the Presentation ViewCreate star schema groupings to provide Reporting Issues Identify conformed vs. non-conformedauthors with logical groupings of query Describe how IBM Cognos BI uses dimensionssubjects cardinality Create star schema groupings to provideWork with Different Query Subject Types Identify reporting traps authors with logical groupings of queryIdentify the effects on generated SQL when Use tools to analyze the model subjectsmodifying query subjects, SQL settings and Model for Predictable Results: Virtual Work with Different Query Subject Typesrelationships Star Schemas Identify the effects on generated SQLSet Security in Framework Manager Model in layers when modifying query subjects, SQLRestrict access to packages Create aliases to avoid ambiguous joins settings and relationshipsCreate and apply security filters Merge query subjects to create as view Set Security in Framework ManagerRestrict access to objects in the model behavior Restrict access to packagesCreate Analysis Objects Model for Predictable Results: Create and apply security filtersSort members for presentation and Consolidate Metadata Restrict access to objects in the modelpredictability Create virtual dimensions to resolve Create Analysis ObjectsManage MUNs in Framework Manager fact-to-fact joins Sort members for presentation andDefine members and member unique names Create a consolidated modeling layer for predictabilityIdentify changes that impact a MUN presentation purposes Manage MUNs in Framework ManagerModel for Drill Through in Framework Consolidate snowflake dimensions with Define members and member uniqueManager model query subjects namesDefine a report drill through Simplify facts by hiding unnecessary Identify changes that impact a MUNDefine a package-based drill through codes Model for Drill Through in FrameworkIdentify drill-through values Calculations and Filters ManagerAdvanced Generated SQL Concepts and Use static filters to reduce the data Define a report drill throughComplex Queries returned Define a package-based drill throughStitch query SQL Use macros and parameters in Identify drill-through valuesConformed and non-conformed dimensions calculations and filters to dynamically Advanced Generated SQL Concepts andin generated SQL control the data returned Complex QueriesMulti-fact/multi-grain stitch query SQL Implement a Time Dimension Stitch query SQLVariances in Report Studio generated SQL Resolve confusion caused by multiple Conformed and non-conformedDimensionally modeled relational SQL relationships between a time dimension dimensions in generated SQLgeneration and another table Multi-fact/multi-grain stitch query SQLCross join SQL Specify Determinants Variances in Report Studio generated SQLVarious results sets for multi-fact queries Create the Presentation View Dimensionally modeled relational SQLUse Advanced Parameterization Techniques Identify conformed vs. non-conformed generationin Framework Manger dimensions Cross join SQLLeverage session, model, and custom Create star schema groupings to provide Various results sets for multi-fact queriesparameters authors with logical groupings of query Use Advanced ParameterizationCreate prompt macros subjects Techniques in Framework MangerLeverage macro functions associated with Work with Different Query Subject Types Leverage session, model, and customsecurity Identify the effects on generated SQL parametersModel Maintenance and Extensibility when modifying query subjects, SQL Create prompt macrosRemap metadata to another source settings and relationships Leverage macro functions associated withImport and link a second data source Set Security in Framework Manager securityRun scripts to automate or update a model Restrict access to packages Model Maintenance and ExtensibilityView lineage Create and apply security filters Remap metadata to another sourceCreate a model report Restrict access to objects in the model Import and link a second data sourceOptimize and Tune Framework Manager Create Analysis Objects Run scripts to automate or update a modelModels Sort members for presentation and View lineageWork in a Multi-Modeler Environment predictability Create a model reportSegment and link a project Manage MUNs in Framework Manager Optimize and Tune Framework ManagerBranch a project and merge results Define members and member unique ModelsManage OLAP Data Sources names Work in a Multi-Modeler EnvironmentPublish an OLAP model Identify changes that impact a MUN Segment and link a projectPublish a model with multiple OLAP data Model for Drill Through in Framework Branch a project and merge resultssources Manager Manage OLAP Data SourcesPublish a model with an OLAP data source Define a report drill through Publish an OLAP modeland a relational data source Define a package-based drill through Publish a model with multiple OLAP dataManage Framework Manager Packages Identify drill-through values sourcesControl model versioning Advanced Generated SQL Concepts and Publish a model with an OLAP data sourceNest packages Complex Queries and a relational data source

Stitch query SQL Manage Framework Manager PackagesConformed and non-conformed Control model versioning


line dimensions in generated SQL Nest packagesDescribe IBM Cognos components Multi-fact/multi-grain stitch query SQLDescribe IBM Cognos architecture at a high Variances in Report Studio generatedlevel SQL lineDefine IBM Cognos groups and roles Dimensionally modeled relational SQL Describe IBM Cognos componentsExplain how to extend IBM Cognos generation Describe IBM Cognos architecture at aIdentify Common Data Structures Cross join SQL high levelExamine relationships and cardinality Various results sets for multi-fact queries Define IBM Cognos groups and rolesIdentify different data traps Use Advanced Parameterization Explain how to extend IBM CognosExamine OLAP data sources Techniques in Framework Manger Identify Common Data StructuresGather Requirements Leverage session, model, and custom Examine relationships and cardinalityDefine reporting requirements parameters Identify different data trapsExplore data sources to identify data access Create prompt macros Examine OLAP data sourcesstrategies Leverage macro functions associated Gather RequirementsCreate a Baseline Project with security Define reporting requirementsDefine a project and its structure Model Maintenance and Extensibility Explore data sources to identify dataDescribe the Framework Manager Remap metadata to another source access strategiesenvironment Import and link a second data source Create a Baseline ProjectCreate a baseline project Run scripts to automate or update a Define a project and its structureEnhance the model with additional metadata model Describe the Framework ManagerPrepare Reusable Metadata View lineage environmentEnsure efficient filters by configuring prompt Create a model report Create a baseline projectproperties Optimize and Tune Framework Manager Enhance the model with additionalModel for Predictable Results: Identify Models metadataReporting Issues Work in a Multi-Modeler Environment Prepare Reusable MetadataDescribe how IBM Cognos BI uses Segment and link a project Ensure efficient filters by configuringcardinality Branch a project and merge results prompt propertiesIdentify reporting traps Manage OLAP Data Sources Model for Predictable Results: IdentifyUse tools to analyze the model Publish an OLAP model Reporting IssuesModel for Predictable Results: Virtual Star Publish a model with multiple OLAP data Describe how IBM Cognos BI usesSchemas sources cardinalityModel in layers Publish a model with an OLAP data Identify reporting trapsCreate aliases to avoid ambiguous joins source and a relational data source Use tools to analyze the modelMerge query subjects to create as view Manage Framework Manager Packages Model for Predictable Results: Virtual Starbehavior Control model versioning SchemasModel for Predictable Results: Consolidate Nest packages Model in layersMetadata Create aliases to avoid ambiguous joinsCreate virtual dimensions to resolve Merge query subjects to create as viewfact-to-fact joins line behaviorCreate a consolidated modeling layer for Describe IBM Cognos components Model for Predictable Results: Consolidatepresentation purposes Describe IBM Cognos architecture at a MetadataConsolidate snowflake dimensions with high level Create virtual dimensions to resolvemodel query subjects Define IBM Cognos groups and roles fact-to-fact joinsSimplify facts by hiding unnecessary codes Explain how to extend IBM Cognos Create a consolidated modeling layer forCalculations and Filters Identify Common Data Structures presentation purposesUse static filters to reduce the data returned Examine relationships and cardinality Consolidate snowflake dimensions withUse macros and parameters in calculations Identify different data traps model query subjectsand filters to dynamically control the data Examine OLAP data sources Simplify facts by hiding unnecessary codesreturned Gather Requirements Calculations and FiltersImplement a Time Dimension Define reporting requirements Use static filters to reduce the dataResolve confusion caused by multiple Explore data sources to identify data returnedrelationships between a time dimension and access strategies Use macros and parameters inanother table Create a Baseline Project calculations and filters to dynamicallySpecify Determinants Define a project and its structure control the data returnedCreate the Presentation View Describe the Framework Manager Implement a Time DimensionIdentify conformed vs. non-conformed environment Resolve confusion caused by multipledimensions Create a baseline project relationships between a time dimensionCreate star schema groupings to provide Enhance the model with additional and another tableauthors with logical groupings of query metadata Specify Determinantssubjects Prepare Reusable Metadata Create the Presentation ViewWork with Different Query Subject Types Ensure efficient filters by configuring Identify conformed vs. non-conformedIdentify the effects on generated SQL when prompt properties dimensionsmodifying query subjects, SQL settings and Model for Predictable Results: Identify Create star schema groupings to providerelationships Reporting Issues authors with logical groupings of querySet Security in Framework Manager Describe how IBM Cognos BI uses subjectsRestrict access to packages cardinality Work with Different Query Subject Types


Create and apply security filters Identify reporting traps Identify the effects on generated SQLRestrict access to objects in the model Use tools to analyze the model when modifying query subjects, SQLCreate Analysis Objects Model for Predictable Results: Virtual settings and relationshipsSort members for presentation and Star Schemas Set Security in Framework Managerpredictability Model in layers Restrict access to packagesManage MUNs in Framework Manager Create aliases to avoid ambiguous joins Create and apply security filtersDefine members and member unique names Merge query subjects to create as view Restrict access to objects in the modelIdentify changes that impact a MUN behavior Create Analysis ObjectsModel for Drill Through in Framework Model for Predictable Results: Sort members for presentation andManager Consolidate Metadata predictabilityDefine a report drill through Create virtual dimensions to resolve Manage MUNs in Framework ManagerDefine a package-based drill through fact-to-fact joins Define members and member uniqueIdentify drill-through values Create a consolidated modeling layer for namesAdvanced Generated SQL Concepts and presentation purposes Identify changes that impact a MUNComplex Queries Consolidate snowflake dimensions with Model for Drill Through in FrameworkStitch query SQL model query subjects ManagerConformed and non-conformed dimensions Simplify facts by hiding unnecessary Define a report drill throughin generated SQL codes Define a package-based drill throughMulti-fact/multi-grain stitch query SQL Calculations and Filters Identify drill-through valuesVariances in Report Studio generated SQL Use static filters to reduce the data Advanced Generated SQL Concepts andDimensionally modeled relational SQL returned Complex Queriesgeneration Use macros and parameters in Stitch query SQLCross join SQL calculations and filters to dynamically Conformed and non-conformedVarious results sets for multi-fact queries control the data returned dimensions in generated SQLUse Advanced Parameterization Techniques Implement a Time Dimension Multi-fact/multi-grain stitch query SQLin Framework Manger Resolve confusion caused by multiple Variances in Report Studio generated SQLLeverage session, model, and custom relationships between a time dimension Dimensionally modeled relational SQLparameters and another table generationCreate prompt macros Specify Determinants Cross join SQLLeverage macro functions associated with Create the Presentation View Various results sets for multi-fact queriessecurity Identify conformed vs. non-conformed Use Advanced ParameterizationModel Maintenance and Extensibility dimensions Techniques in Framework MangerRemap metadata to another source Create star schema groupings to provide Leverage session, model, and customImport and link a second data source authors with logical groupings of query parametersRun scripts to automate or update a model subjects Create prompt macrosView lineage Work with Different Query Subject Types Leverage macro functions associated withCreate a model report Identify the effects on generated SQL securityOptimize and Tune Framework Manager when modifying query subjects, SQL Model Maintenance and ExtensibilityModels settings and relationships Remap metadata to another sourceWork in a Multi-Modeler Environment Set Security in Framework Manager Import and link a second data sourceSegment and link a project Restrict access to packages Run scripts to automate or update a modelBranch a project and merge results Create and apply security filters View lineageManage OLAP Data Sources Restrict access to objects in the model Create a model reportPublish an OLAP model Create Analysis Objects Optimize and Tune Framework ManagerPublish a model with multiple OLAP data Sort members for presentation and Modelssources predictability Work in a Multi-Modeler EnvironmentPublish a model with an OLAP data source Manage MUNs in Framework Manager Segment and link a projectand a relational data source Define members and member unique Branch a project and merge resultsManage Framework Manager Packages names Manage OLAP Data SourcesControl model versioning Identify changes that impact a MUN Publish an OLAP modelNest packages Model for Drill Through in Framework Publish a model with multiple OLAP data

Manager sourcesDefine a report drill through Publish a model with an OLAP data source

line Define a package-based drill through and a relational data sourceDescribe IBM Cognos components Identify drill-through values Manage Framework Manager PackagesDescribe IBM Cognos architecture at a high Advanced Generated SQL Concepts and Control model versioninglevel Complex Queries Nest packagesDefine IBM Cognos groups and roles Stitch query SQLExplain how to extend IBM Cognos Conformed and non-conformedIdentify Common Data Structures dimensions in generated SQL lineExamine relationships and cardinality Multi-fact/multi-grain stitch query SQL Describe IBM Cognos componentsIdentify different data traps Variances in Report Studio generated Describe IBM Cognos architecture at aExamine OLAP data sources SQL high levelGather Requirements Dimensionally modeled relational SQL Define IBM Cognos groups and rolesDefine reporting requirements generation Explain how to extend IBM CognosExplore data sources to identify data access Cross join SQL Identify Common Data Structures


strategies Various results sets for multi-fact queries Examine relationships and cardinalityCreate a Baseline Project Use Advanced Parameterization Identify different data trapsDefine a project and its structure Techniques in Framework Manger Examine OLAP data sourcesDescribe the Framework Manager Leverage session, model, and custom Gather Requirementsenvironment parameters Define reporting requirementsCreate a baseline project Create prompt macros Explore data sources to identify dataEnhance the model with additional metadata Leverage macro functions associated access strategiesPrepare Reusable Metadata with security Create a Baseline ProjectEnsure efficient filters by configuring prompt Model Maintenance and Extensibility Define a project and its structureproperties Remap metadata to another source Describe the Framework ManagerModel for Predictable Results: Identify Import and link a second data source environmentReporting Issues Run scripts to automate or update a Create a baseline projectDescribe how IBM Cognos BI uses model Enhance the model with additionalcardinality View lineage metadataIdentify reporting traps Create a model report Prepare Reusable MetadataUse tools to analyze the model Optimize and Tune Framework Manager Ensure efficient filters by configuringModel for Predictable Results: Virtual Star Models prompt propertiesSchemas Work in a Multi-Modeler Environment Model for Predictable Results: IdentifyModel in layers Segment and link a project Reporting IssuesCreate aliases to avoid ambiguous joins Branch a project and merge results Describe how IBM Cognos BI usesMerge query subjects to create as view Manage OLAP Data Sources cardinalitybehavior Publish an OLAP model Identify reporting trapsModel for Predictable Results: Consolidate Publish a model with multiple OLAP data Use tools to analyze the modelMetadata sources Model for Predictable Results: Virtual StarCreate virtual dimensions to resolve Publish a model with an OLAP data Schemasfact-to-fact joins source and a relational data source Model in layersCreate a consolidated modeling layer for Manage Framework Manager Packages Create aliases to avoid ambiguous joinspresentation purposes Control model versioning Merge query subjects to create as viewConsolidate snowflake dimensions with Nest packages behaviormodel query subjects Model for Predictable Results: ConsolidateSimplify facts by hiding unnecessary codes MetadataCalculations and Filters line Create virtual dimensions to resolveUse static filters to reduce the data returned Discuss IBM Cognos and Performance fact-to-fact joinsUse macros and parameters in calculations Management Create a consolidated modeling layer forand filters to dynamically control the data Examine the characteristics of presentation purposesreturned operational databases and databases Consolidate snowflake dimensions withImplement a Time Dimension designed for reporting model query subjectsResolve confusion caused by multiple Examine key modeling recommendations Simplify facts by hiding unnecessary codesrelationships between a time dimension and Examine the IBM Cognos BI and Calculations and Filtersanother table Framework Manager workflow processes Use static filters to reduce the dataSpecify Determinants Verify relationships and query item returnedCreate the Presentation View properties Use macros and parameters inIdentify conformed vs. non-conformed Describe multi-fact queries and when full calculations and filters to dynamicallydimensions outer joins are appropriate control the data returnedCreate star schema groupings to provide Identify the advantages of modeling Implement a Time Dimensionauthors with logical groupings of query metadata as a star schema Resolve confusion caused by multiplesubjects Create virtual facts to simplify writing relationships between a time dimensionWork with Different Query Subject Types queries and another tableIdentify the effects on generated SQL when Use calculations to create Specify Determinantsmodifying query subjects, SQL settings and commonly-needed query items for Create the Presentation Viewrelationships authors Identify conformed vs. non-conformedSet Security in Framework Manager Make time-based queries simple to dimensionsRestrict access to packages author by implementing a time dimension Create star schema groupings to provideCreate and apply security filters Use determinants to specify multiple authors with logical groupings of queryRestrict access to objects in the model levels of granularity and prevent subjectsCreate Analysis Objects double-counting Work with Different Query Subject TypesSort members for presentation and Identify the dimensions associated with a Identify the effects on generated SQLpredictability fact table when modifying query subjects, SQLManage MUNs in Framework Manager Identify key differences and settings and relationshipsDefine members and member unique names recommendations for using data source, Set Security in Framework ManagerIdentify changes that impact a MUN model, and stored procedure query Restrict access to packagesModel for Drill Through in Framework subjects Create and apply security filtersManager Examine the IBM Cognos BI security Restrict access to objects in the modelDefine a report drill through environment Create Analysis ObjectsDefine a package-based drill through Apply dimensional information to Sort members for presentation andIdentify drill-through values relational Metadata to enable OLAP-style predictability


Advanced Generated SQL Concepts and queries Manage MUNs in Framework ManagerComplex Queries Describe model types and data entities Define members and member uniqueStitch query SQL Identify conformed values between data namesConformed and non-conformed dimensions sources Identify changes that impact a MUNin generated SQL Governors that affect SQL generation Model for Drill Through in FrameworkMulti-fact/multi-grain stitch query SQL Identify session and model parameters ManagerVariances in Report Studio generated SQL Perform basic maintenance and Define a report drill throughDimensionally modeled relational SQL management on a model Define a package-based drill throughgeneration Identify and implement techniques to Identify drill-through valuesCross join SQL optimize and tune your Framework Advanced Generated SQL Concepts andVarious results sets for multi-fact queries Manager models Complex QueriesUse Advanced Parameterization Techniques Implement repository control Stitch query SQLin Framework Manger Connect to an OLAP data source (cube) Conformed and non-conformedLeverage session, model, and custom in a Framework Manager project dimensions in generated SQLparameters Specify package languages and function Multi-fact/multi-grain stitch query SQLCreate prompt macros sets Variances in Report Studio generated SQLLeverage macro functions associated with Dimensionally modeled relational SQLsecurity generationModel Maintenance and Extensibility line Cross join SQLRemap metadata to another source Describe IBM Cognos components Various results sets for multi-fact queriesImport and link a second data source Describe IBM Cognos architecture at a Use Advanced ParameterizationRun scripts to automate or update a model high level Techniques in Framework MangerView lineage Define IBM Cognos groups and roles Leverage session, model, and customCreate a model report Explain how to extend IBM Cognos parametersOptimize and Tune Framework Manager Identify Common Data Structures Create prompt macrosModels Examine relationships and cardinality Leverage macro functions associated withWork in a Multi-Modeler Environment Identify different data traps securitySegment and link a project Examine OLAP data sources Model Maintenance and ExtensibilityBranch a project and merge results Gather Requirements Remap metadata to another sourceManage OLAP Data Sources Define reporting requirements Import and link a second data sourcePublish an OLAP model Explore data sources to identify data Run scripts to automate or update a modelPublish a model with multiple OLAP data access strategies View lineagesources Create a Baseline Project Create a model reportPublish a model with an OLAP data source Define a project and its structure Optimize and Tune Framework Managerand a relational data source Describe the Framework Manager ModelsManage Framework Manager Packages environment Work in a Multi-Modeler EnvironmentControl model versioning Create a baseline project Segment and link a projectNest packages Enhance the model with additional Branch a project and merge results

metadata Manage OLAP Data SourcesPrepare Reusable Metadata Publish an OLAP model

line Ensure efficient filters by configuring Publish a model with multiple OLAP dataDiscuss IBM Cognos and Performance prompt properties sourcesManagement Model for Predictable Results: Identify Publish a model with an OLAP data sourceExamine the characteristics of operational Reporting Issues and a relational data sourcedatabases and databases designed for Describe how IBM Cognos BI uses Manage Framework Manager Packagesreporting cardinality Control model versioningExamine key modeling recommendations Identify reporting traps Nest packagesExamine the IBM Cognos BI and Framework Use tools to analyze the modelManager workflow processes Model for Predictable Results: VirtualVerify relationships and query item Star Schemas lineproperties Model in layers Describe IBM Cognos componentsDescribe multi-fact queries and when full Create aliases to avoid ambiguous joins Describe IBM Cognos architecture at aouter joins are appropriate Merge query subjects to create as view high levelIdentify the advantages of modeling behavior Define IBM Cognos groups and rolesmetadata as a star schema Model for Predictable Results: Explain how to extend IBM CognosCreate virtual facts to simplify writing queries Consolidate Metadata Identify Common Data StructuresUse calculations to create Create virtual dimensions to resolve Examine relationships and cardinalitycommonly-needed query items for authors fact-to-fact joins Identify different data trapsMake time-based queries simple to author Create a consolidated modeling layer for Examine OLAP data sourcesby implementing a time dimension presentation purposes Gather RequirementsUse determinants to specify multiple levels Consolidate snowflake dimensions with Define reporting requirementsof granularity and prevent double-counting model query subjects Explore data sources to identify dataIdentify the dimensions associated with a Simplify facts by hiding unnecessary access strategiesfact table codes Create a Baseline ProjectIdentify key differences and Calculations and Filters Define a project and its structurerecommendations for using data source, Use static filters to reduce the data Describe the Framework Manager


model, and stored procedure query subjects returned environmentExamine the IBM Cognos BI security Use macros and parameters in Create a baseline projectenvironment calculations and filters to dynamically Enhance the model with additionalApply dimensional information to relational control the data returned metadataMetadata to enable OLAP-style queries Implement a Time Dimension Prepare Reusable MetadataDescribe model types and data entities Resolve confusion caused by multiple Ensure efficient filters by configuringIdentify conformed values between data relationships between a time dimension prompt propertiessources and another table Model for Predictable Results: IdentifyGovernors that affect SQL generation Specify Determinants Reporting IssuesIdentify session and model parameters Create the Presentation View Describe how IBM Cognos BI usesPerform basic maintenance and Identify conformed vs. non-conformed cardinalitymanagement on a model dimensions Identify reporting trapsIdentify and implement techniques to Create star schema groupings to provide Use tools to analyze the modeloptimize and tune your Framework Manager authors with logical groupings of query Model for Predictable Results: Virtual Starmodels subjects SchemasImplement repository control Work with Different Query Subject Types Model in layersConnect to an OLAP data source (cube) in a Identify the effects on generated SQL Create aliases to avoid ambiguous joinsFramework Manager project when modifying query subjects, SQL Merge query subjects to create as viewSpecify package languages and function settings and relationships behaviorsets Set Security in Framework Manager Model for Predictable Results: Consolidate

Restrict access to packages MetadataCreate and apply security filters Create virtual dimensions to resolve

line Restrict access to objects in the model fact-to-fact joinsDescribe IBM Cognos components Create Analysis Objects Create a consolidated modeling layer forDescribe IBM Cognos architecture at a high Sort members for presentation and presentation purposeslevel predictability Consolidate snowflake dimensions withDefine IBM Cognos groups and roles Manage MUNs in Framework Manager model query subjectsExplain how to extend IBM Cognos Define members and member unique Simplify facts by hiding unnecessary codesIdentify Common Data Structures names Calculations and FiltersExamine relationships and cardinality Identify changes that impact a MUN Use static filters to reduce the dataIdentify different data traps Model for Drill Through in Framework returnedExamine OLAP data sources Manager Use macros and parameters inGather Requirements Define a report drill through calculations and filters to dynamicallyDefine reporting requirements Define a package-based drill through control the data returnedExplore data sources to identify data access Identify drill-through values Implement a Time Dimensionstrategies Advanced Generated SQL Concepts and Resolve confusion caused by multipleCreate a Baseline Project Complex Queries relationships between a time dimensionDefine a project and its structure Stitch query SQL and another tableDescribe the Framework Manager Conformed and non-conformed Specify Determinantsenvironment dimensions in generated SQL Create the Presentation ViewCreate a baseline project Multi-fact/multi-grain stitch query SQL Identify conformed vs. non-conformedEnhance the model with additional metadata Variances in Report Studio generated dimensionsPrepare Reusable Metadata SQL Create star schema groupings to provideEnsure efficient filters by configuring prompt Dimensionally modeled relational SQL authors with logical groupings of queryproperties generation subjectsModel for Predictable Results: Identify Cross join SQL Work with Different Query Subject TypesReporting Issues Various results sets for multi-fact queries Identify the effects on generated SQLDescribe how IBM Cognos BI uses Use Advanced Parameterization when modifying query subjects, SQLcardinality Techniques in Framework Manger settings and relationshipsIdentify reporting traps Leverage session, model, and custom Set Security in Framework ManagerUse tools to analyze the model parameters Restrict access to packagesModel for Predictable Results: Virtual Star Create prompt macros Create and apply security filtersSchemas Leverage macro functions associated Restrict access to objects in the modelModel in layers with security Create Analysis ObjectsCreate aliases to avoid ambiguous joins Model Maintenance and Extensibility Sort members for presentation andMerge query subjects to create as view Remap metadata to another source predictabilitybehavior Import and link a second data source Manage MUNs in Framework ManagerModel for Predictable Results: Consolidate Run scripts to automate or update a Define members and member uniqueMetadata model namesCreate virtual dimensions to resolve View lineage Identify changes that impact a MUNfact-to-fact joins Create a model report Model for Drill Through in FrameworkCreate a consolidated modeling layer for Optimize and Tune Framework Manager Managerpresentation purposes Models Define a report drill throughConsolidate snowflake dimensions with Work in a Multi-Modeler Environment Define a package-based drill throughmodel query subjects Segment and link a project Identify drill-through valuesSimplify facts by hiding unnecessary codes Branch a project and merge results Advanced Generated SQL Concepts and


Calculations and Filters Manage OLAP Data Sources Complex QueriesUse static filters to reduce the data returned Publish an OLAP model Stitch query SQLUse macros and parameters in calculations Publish a model with multiple OLAP data Conformed and non-conformedand filters to dynamically control the data sources dimensions in generated SQLreturned Publish a model with an OLAP data Multi-fact/multi-grain stitch query SQLImplement a Time Dimension source and a relational data source Variances in Report Studio generated SQLResolve confusion caused by multiple Manage Framework Manager Packages Dimensionally modeled relational SQLrelationships between a time dimension and Control model versioning generationanother table Nest packages Cross join SQLSpecify Determinants Various results sets for multi-fact queriesCreate the Presentation View Use Advanced ParameterizationIdentify conformed vs. non-conformed line Techniques in Framework Mangerdimensions Describe IBM Cognos components Leverage session, model, and customCreate star schema groupings to provide Describe IBM Cognos architecture at a parametersauthors with logical groupings of query high level Create prompt macrossubjects Define IBM Cognos groups and roles Leverage macro functions associated withWork with Different Query Subject Types Explain how to extend IBM Cognos securityIdentify the effects on generated SQL when Identify Common Data Structures Model Maintenance and Extensibilitymodifying query subjects, SQL settings and Examine relationships and cardinality Remap metadata to another sourcerelationships Identify different data traps Import and link a second data sourceSet Security in Framework Manager Examine OLAP data sources Run scripts to automate or update a modelRestrict access to packages Gather Requirements View lineageCreate and apply security filters Define reporting requirements Create a model reportRestrict access to objects in the model Explore data sources to identify data Optimize and Tune Framework ManagerCreate Analysis Objects access strategies ModelsSort members for presentation and Create a Baseline Project Work in a Multi-Modeler Environmentpredictability Define a project and its structure Segment and link a projectManage MUNs in Framework Manager Describe the Framework Manager Branch a project and merge resultsDefine members and member unique names environment Manage OLAP Data SourcesIdentify changes that impact a MUN Create a baseline project Publish an OLAP modelModel for Drill Through in Framework Enhance the model with additional Publish a model with multiple OLAP dataManager metadata sourcesDefine a report drill through Prepare Reusable Metadata Publish a model with an OLAP data sourceDefine a package-based drill through Ensure efficient filters by configuring and a relational data sourceIdentify drill-through values prompt properties Manage Framework Manager PackagesAdvanced Generated SQL Concepts and Model for Predictable Results: Identify Control model versioningComplex Queries Reporting Issues Nest packagesStitch query SQL Describe how IBM Cognos BI usesConformed and non-conformed dimensions cardinalityin generated SQL Identify reporting traps lineMulti-fact/multi-grain stitch query SQL Use tools to analyze the model Describe IBM Cognos componentsVariances in Report Studio generated SQL Model for Predictable Results: Virtual Describe IBM Cognos architecture at aDimensionally modeled relational SQL Star Schemas high levelgeneration Model in layers Define IBM Cognos groups and rolesCross join SQL Create aliases to avoid ambiguous joins Explain how to extend IBM CognosVarious results sets for multi-fact queries Merge query subjects to create as view Identify Common Data StructuresUse Advanced Parameterization Techniques behavior Examine relationships and cardinalityin Framework Manger Model for Predictable Results: Identify different data trapsLeverage session, model, and custom Consolidate Metadata Examine OLAP data sourcesparameters Create virtual dimensions to resolve Gather RequirementsCreate prompt macros fact-to-fact joins Define reporting requirementsLeverage macro functions associated with Create a consolidated modeling layer for Explore data sources to identify datasecurity presentation purposes access strategiesModel Maintenance and Extensibility Consolidate snowflake dimensions with Create a Baseline ProjectRemap metadata to another source model query subjects Define a project and its structureImport and link a second data source Simplify facts by hiding unnecessary Describe the Framework ManagerRun scripts to automate or update a model codes environmentView lineage Calculations and Filters Create a baseline projectCreate a model report Use static filters to reduce the data Enhance the model with additionalOptimize and Tune Framework Manager returned metadataModels Use macros and parameters in Prepare Reusable MetadataWork in a Multi-Modeler Environment calculations and filters to dynamically Ensure efficient filters by configuringSegment and link a project control the data returned prompt propertiesBranch a project and merge results Implement a Time Dimension Model for Predictable Results: IdentifyManage OLAP Data Sources Resolve confusion caused by multiple Reporting IssuesPublish an OLAP model relationships between a time dimension Describe how IBM Cognos BI uses


Publish a model with multiple OLAP data and another table cardinalitysources Specify Determinants Identify reporting trapsPublish a model with an OLAP data source Create the Presentation View Use tools to analyze the modeland a relational data source Identify conformed vs. non-conformed Model for Predictable Results: Virtual StarManage Framework Manager Packages dimensions SchemasControl model versioning Create star schema groupings to provide Model in layersNest packages authors with logical groupings of query Create aliases to avoid ambiguous joins

subjects Merge query subjects to create as viewWork with Different Query Subject Types behavior

line Identify the effects on generated SQL Model for Predictable Results: ConsolidateDescribe IBM Cognos components when modifying query subjects, SQL MetadataDescribe IBM Cognos architecture at a high settings and relationships Create virtual dimensions to resolvelevel Set Security in Framework Manager fact-to-fact joinsDefine IBM Cognos groups and roles Restrict access to packages Create a consolidated modeling layer forExplain how to extend IBM Cognos Create and apply security filters presentation purposesIdentify Common Data Structures Restrict access to objects in the model Consolidate snowflake dimensions withExamine relationships and cardinality Create Analysis Objects model query subjectsIdentify different data traps Sort members for presentation and Simplify facts by hiding unnecessary codesExamine OLAP data sources predictability Calculations and FiltersGather Requirements Manage MUNs in Framework Manager Use static filters to reduce the dataDefine reporting requirements Define members and member unique returnedExplore data sources to identify data access names Use macros and parameters instrategies Identify changes that impact a MUN calculations and filters to dynamicallyCreate a Baseline Project Model for Drill Through in Framework control the data returnedDefine a project and its structure Manager Implement a Time DimensionDescribe the Framework Manager Define a report drill through Resolve confusion caused by multipleenvironment Define a package-based drill through relationships between a time dimensionCreate a baseline project Identify drill-through values and another tableEnhance the model with additional metadata Advanced Generated SQL Concepts and Specify DeterminantsPrepare Reusable Metadata Complex Queries Create the Presentation ViewEnsure efficient filters by configuring prompt Stitch query SQL Identify conformed vs. non-conformedproperties Conformed and non-conformed dimensionsModel for Predictable Results: Identify dimensions in generated SQL Create star schema groupings to provideReporting Issues Multi-fact/multi-grain stitch query SQL authors with logical groupings of queryDescribe how IBM Cognos BI uses Variances in Report Studio generated subjectscardinality SQL Work with Different Query Subject TypesIdentify reporting traps Dimensionally modeled relational SQL Identify the effects on generated SQLUse tools to analyze the model generation when modifying query subjects, SQLModel for Predictable Results: Virtual Star Cross join SQL settings and relationshipsSchemas Various results sets for multi-fact queries Set Security in Framework ManagerModel in layers Use Advanced Parameterization Restrict access to packagesCreate aliases to avoid ambiguous joins Techniques in Framework Manger Create and apply security filtersMerge query subjects to create as view Leverage session, model, and custom Restrict access to objects in the modelbehavior parameters Create Analysis ObjectsModel for Predictable Results: Consolidate Create prompt macros Sort members for presentation andMetadata Leverage macro functions associated predictabilityCreate virtual dimensions to resolve with security Manage MUNs in Framework Managerfact-to-fact joins Model Maintenance and Extensibility Define members and member uniqueCreate a consolidated modeling layer for Remap metadata to another source namespresentation purposes Import and link a second data source Identify changes that impact a MUNConsolidate snowflake dimensions with Run scripts to automate or update a Model for Drill Through in Frameworkmodel query subjects model ManagerSimplify facts by hiding unnecessary codes View lineage Define a report drill throughCalculations and Filters Create a model report Define a package-based drill throughUse static filters to reduce the data returned Optimize and Tune Framework Manager Identify drill-through valuesUse macros and parameters in calculations Models Advanced Generated SQL Concepts andand filters to dynamically control the data Work in a Multi-Modeler Environment Complex Queriesreturned Segment and link a project Stitch query SQLImplement a Time Dimension Branch a project and merge results Conformed and non-conformedResolve confusion caused by multiple Manage OLAP Data Sources dimensions in generated SQLrelationships between a time dimension and Publish an OLAP model Multi-fact/multi-grain stitch query SQLanother table Publish a model with multiple OLAP data Variances in Report Studio generated SQLSpecify Determinants sources Dimensionally modeled relational SQLCreate the Presentation View Publish a model with an OLAP data generationIdentify conformed vs. non-conformed source and a relational data source Cross join SQLdimensions Manage Framework Manager Packages Various results sets for multi-fact queries


Create star schema groupings to provide Control model versioning Use Advanced Parameterizationauthors with logical groupings of query Nest packages Techniques in Framework Mangersubjects Leverage session, model, and customWork with Different Query Subject Types parametersIdentify the effects on generated SQL when line Create prompt macrosmodifying query subjects, SQL settings and Describe IBM Cognos components Leverage macro functions associated withrelationships Describe IBM Cognos architecture at a securitySet Security in Framework Manager high level Model Maintenance and ExtensibilityRestrict access to packages Define IBM Cognos groups and roles Remap metadata to another sourceCreate and apply security filters Explain how to extend IBM Cognos Import and link a second data sourceRestrict access to objects in the model Identify Common Data Structures Run scripts to automate or update a modelCreate Analysis Objects Examine relationships and cardinality View lineageSort members for presentation and Identify different data traps Create a model reportpredictability Examine OLAP data sources Optimize and Tune Framework ManagerManage MUNs in Framework Manager Gather Requirements ModelsDefine members and member unique names Define reporting requirements Work in a Multi-Modeler EnvironmentIdentify changes that impact a MUN Explore data sources to identify data Segment and link a projectModel for Drill Through in Framework access strategies Branch a project and merge resultsManager Create a Baseline Project Manage OLAP Data SourcesDefine a report drill through Define a project and its structure Publish an OLAP modelDefine a package-based drill through Describe the Framework Manager Publish a model with multiple OLAP dataIdentify drill-through values environment sourcesAdvanced Generated SQL Concepts and Create a baseline project Publish a model with an OLAP data sourceComplex Queries Enhance the model with additional and a relational data sourceStitch query SQL metadata Manage Framework Manager PackagesConformed and non-conformed dimensions Prepare Reusable Metadata Control model versioningin generated SQL Ensure efficient filters by configuring Nest packagesMulti-fact/multi-grain stitch query SQL prompt propertiesVariances in Report Studio generated SQL Model for Predictable Results: IdentifyDimensionally modeled relational SQL Reporting Issues linegeneration Describe how IBM Cognos BI uses Discuss IBM Cognos and PerformanceCross join SQL cardinality ManagementVarious results sets for multi-fact queries Identify reporting traps Examine the characteristics of operationalUse Advanced Parameterization Techniques Use tools to analyze the model databases and databases designed forin Framework Manger Model for Predictable Results: Virtual reportingLeverage session, model, and custom Star Schemas Examine key modeling recommendationsparameters Model in layers Examine the IBM Cognos BI andCreate prompt macros Create aliases to avoid ambiguous joins Framework Manager workflow processesLeverage macro functions associated with Merge query subjects to create as view Verify relationships and query itemsecurity behavior propertiesModel Maintenance and Extensibility Model for Predictable Results: Describe multi-fact queries and when fullRemap metadata to another source Consolidate Metadata outer joins are appropriateImport and link a second data source Create virtual dimensions to resolve Identify the advantages of modelingRun scripts to automate or update a model fact-to-fact joins metadata as a star schemaView lineage Create a consolidated modeling layer for Create virtual facts to simplify writingCreate a model report presentation purposes queriesOptimize and Tune Framework Manager Consolidate snowflake dimensions with Use calculations to createModels model query subjects commonly-needed query items for authorsWork in a Multi-Modeler Environment Simplify facts by hiding unnecessary Make time-based queries simple to authorSegment and link a project codes by implementing a time dimensionBranch a project and merge results Calculations and Filters Use determinants to specify multiple levelsManage OLAP Data Sources Use static filters to reduce the data of granularity and prevent double-countingPublish an OLAP model returned Identify the dimensions associated with aPublish a model with multiple OLAP data Use macros and parameters in fact tablesources calculations and filters to dynamically Identify key differences andPublish a model with an OLAP data source control the data returned recommendations for using data source,and a relational data source Implement a Time Dimension model, and stored procedure queryManage Framework Manager Packages Resolve confusion caused by multiple subjectsControl model versioning relationships between a time dimension Examine the IBM Cognos BI securityNest packages and another table environment

Specify Determinants Apply dimensional information to relationalCreate the Presentation View Metadata to enable OLAP-style queries

line Identify conformed vs. non-conformed Describe model types and data entitiesDiscuss IBM Cognos and Performance dimensions Identify conformed values between dataManagement Create star schema groupings to provide sourcesExamine the characteristics of operational authors with logical groupings of query Governors that affect SQL generation


databases and databases designed for subjects Identify session and model parametersreporting Work with Different Query Subject Types Perform basic maintenance andExamine key modeling recommendations Identify the effects on generated SQL management on a modelExamine the IBM Cognos BI and Framework when modifying query subjects, SQL Identify and implement techniques toManager workflow processes settings and relationships optimize and tune your FrameworkVerify relationships and query item Set Security in Framework Manager Manager modelsproperties Restrict access to packages Implement repository controlDescribe multi-fact queries and when full Create and apply security filters Connect to an OLAP data source (cube) inouter joins are appropriate Restrict access to objects in the model a Framework Manager projectIdentify the advantages of modeling Create Analysis Objects Specify package languages and functionmetadata as a star schema Sort members for presentation and setsCreate virtual facts to simplify writing queries predictabilityUse calculations to create Manage MUNs in Framework Managercommonly-needed query items for authors Define members and member unique lineMake time-based queries simple to author names Describe IBM Cognos componentsby implementing a time dimension Identify changes that impact a MUN Describe IBM Cognos architecture at aUse determinants to specify multiple levels Model for Drill Through in Framework high levelof granularity and prevent double-counting Manager Define IBM Cognos groups and rolesIdentify the dimensions associated with a Define a report drill through Explain how to extend IBM Cognosfact table Define a package-based drill through Identify Common Data StructuresIdentify key differences and Identify drill-through values Examine relationships and cardinalityrecommendations for using data source, Advanced Generated SQL Concepts and Identify different data trapsmodel, and stored procedure query subjects Complex Queries Examine OLAP data sourcesExamine the IBM Cognos BI security Stitch query SQL Gather Requirementsenvironment Conformed and non-conformed Define reporting requirementsApply dimensional information to relational dimensions in generated SQL Explore data sources to identify dataMetadata to enable OLAP-style queries Multi-fact/multi-grain stitch query SQL access strategiesDescribe model types and data entities Variances in Report Studio generated Create a Baseline ProjectIdentify conformed values between data SQL Define a project and its structuresources Dimensionally modeled relational SQL Describe the Framework ManagerGovernors that affect SQL generation generation environmentIdentify session and model parameters Cross join SQL Create a baseline projectPerform basic maintenance and Various results sets for multi-fact queries Enhance the model with additionalmanagement on a model Use Advanced Parameterization metadataIdentify and implement techniques to Techniques in Framework Manger Prepare Reusable Metadataoptimize and tune your Framework Manager Leverage session, model, and custom Ensure efficient filters by configuringmodels parameters prompt propertiesImplement repository control Create prompt macros Model for Predictable Results: IdentifyConnect to an OLAP data source (cube) in a Leverage macro functions associated Reporting IssuesFramework Manager project with security Describe how IBM Cognos BI usesSpecify package languages and function Model Maintenance and Extensibility cardinalitysets Remap metadata to another source Identify reporting traps

Import and link a second data source Use tools to analyze the modelRun scripts to automate or update a Model for Predictable Results: Virtual Star

line model SchemasDescribe IBM Cognos components View lineage Model in layersDescribe IBM Cognos architecture at a high Create a model report Create aliases to avoid ambiguous joinslevel Optimize and Tune Framework Manager Merge query subjects to create as viewDefine IBM Cognos groups and roles Models behaviorExplain how to extend IBM Cognos Work in a Multi-Modeler Environment Model for Predictable Results: ConsolidateIdentify Common Data Structures Segment and link a project MetadataExamine relationships and cardinality Branch a project and merge results Create virtual dimensions to resolveIdentify different data traps Manage OLAP Data Sources fact-to-fact joinsExamine OLAP data sources Publish an OLAP model Create a consolidated modeling layer forGather Requirements Publish a model with multiple OLAP data presentation purposesDefine reporting requirements sources Consolidate snowflake dimensions withExplore data sources to identify data access Publish a model with an OLAP data model query subjectsstrategies source and a relational data source Simplify facts by hiding unnecessary codesCreate a Baseline Project Manage Framework Manager Packages Calculations and FiltersDefine a project and its structure Control model versioning Use static filters to reduce the dataDescribe the Framework Manager Nest packages returnedenvironment Use macros and parameters inCreate a baseline project calculations and filters to dynamicallyEnhance the model with additional metadata line control the data returnedPrepare Reusable Metadata Describe IBM Cognos components Implement a Time DimensionEnsure efficient filters by configuring prompt Describe IBM Cognos architecture at a Resolve confusion caused by multiple


properties high level relationships between a time dimensionModel for Predictable Results: Identify Define IBM Cognos groups and roles and another tableReporting Issues Explain how to extend IBM Cognos Specify DeterminantsDescribe how IBM Cognos BI uses Identify Common Data Structures Create the Presentation Viewcardinality Examine relationships and cardinality Identify conformed vs. non-conformedIdentify reporting traps Identify different data traps dimensionsUse tools to analyze the model Examine OLAP data sources Create star schema groupings to provideModel for Predictable Results: Virtual Star Gather Requirements authors with logical groupings of querySchemas Define reporting requirements subjectsModel in layers Explore data sources to identify data Work with Different Query Subject TypesCreate aliases to avoid ambiguous joins access strategies Identify the effects on generated SQLMerge query subjects to create as view Create a Baseline Project when modifying query subjects, SQLbehavior Define a project and its structure settings and relationshipsModel for Predictable Results: Consolidate Describe the Framework Manager Set Security in Framework ManagerMetadata environment Restrict access to packagesCreate virtual dimensions to resolve Create a baseline project Create and apply security filtersfact-to-fact joins Enhance the model with additional Restrict access to objects in the modelCreate a consolidated modeling layer for metadata Create Analysis Objectspresentation purposes Prepare Reusable Metadata Sort members for presentation andConsolidate snowflake dimensions with Ensure efficient filters by configuring predictabilitymodel query subjects prompt properties Manage MUNs in Framework ManagerSimplify facts by hiding unnecessary codes Model for Predictable Results: Identify Define members and member uniqueCalculations and Filters Reporting Issues namesUse static filters to reduce the data returned Describe how IBM Cognos BI uses Identify changes that impact a MUNUse macros and parameters in calculations cardinality Model for Drill Through in Frameworkand filters to dynamically control the data Identify reporting traps Managerreturned Use tools to analyze the model Define a report drill throughImplement a Time Dimension Model for Predictable Results: Virtual Define a package-based drill throughResolve confusion caused by multiple Star Schemas Identify drill-through valuesrelationships between a time dimension and Model in layers Advanced Generated SQL Concepts andanother table Create aliases to avoid ambiguous joins Complex QueriesSpecify Determinants Merge query subjects to create as view Stitch query SQLCreate the Presentation View behavior Conformed and non-conformedIdentify conformed vs. non-conformed Model for Predictable Results: dimensions in generated SQLdimensions Consolidate Metadata Multi-fact/multi-grain stitch query SQLCreate star schema groupings to provide Create virtual dimensions to resolve Variances in Report Studio generated SQLauthors with logical groupings of query fact-to-fact joins Dimensionally modeled relational SQLsubjects Create a consolidated modeling layer for generationWork with Different Query Subject Types presentation purposes Cross join SQLIdentify the effects on generated SQL when Consolidate snowflake dimensions with Various results sets for multi-fact queriesmodifying query subjects, SQL settings and model query subjects Use Advanced Parameterizationrelationships Simplify facts by hiding unnecessary Techniques in Framework MangerSet Security in Framework Manager codes Leverage session, model, and customRestrict access to packages Calculations and Filters parametersCreate and apply security filters Use static filters to reduce the data Create prompt macrosRestrict access to objects in the model returned Leverage macro functions associated withCreate Analysis Objects Use macros and parameters in securitySort members for presentation and calculations and filters to dynamically Model Maintenance and Extensibilitypredictability control the data returned Remap metadata to another sourceManage MUNs in Framework Manager Implement a Time Dimension Import and link a second data sourceDefine members and member unique names Resolve confusion caused by multiple Run scripts to automate or update a modelIdentify changes that impact a MUN relationships between a time dimension View lineageModel for Drill Through in Framework and another table Create a model reportManager Specify Determinants Optimize and Tune Framework ManagerDefine a report drill through Create the Presentation View ModelsDefine a package-based drill through Identify conformed vs. non-conformed Work in a Multi-Modeler EnvironmentIdentify drill-through values dimensions Segment and link a projectAdvanced Generated SQL Concepts and Create star schema groupings to provide Branch a project and merge resultsComplex Queries authors with logical groupings of query Manage OLAP Data SourcesStitch query SQL subjects Publish an OLAP modelConformed and non-conformed dimensions Work with Different Query Subject Types Publish a model with multiple OLAP datain generated SQL Identify the effects on generated SQL sourcesMulti-fact/multi-grain stitch query SQL when modifying query subjects, SQL Publish a model with an OLAP data sourceVariances in Report Studio generated SQL settings and relationships and a relational data sourceDimensionally modeled relational SQL Set Security in Framework Manager Manage Framework Manager Packagesgeneration Restrict access to packages Control model versioning


Cross join SQL Create and apply security filters Nest packagesVarious results sets for multi-fact queries Restrict access to objects in the modelUse Advanced Parameterization Techniques Create Analysis Objectsin Framework Manger Sort members for presentation and lineLeverage session, model, and custom predictability Discuss IBM Cognos and Performanceparameters Manage MUNs in Framework Manager ManagementCreate prompt macros Define members and member unique Examine the characteristics of operationalLeverage macro functions associated with names databases and databases designed forsecurity Identify changes that impact a MUN reportingModel Maintenance and Extensibility Model for Drill Through in Framework Examine key modeling recommendationsRemap metadata to another source Manager Examine the IBM Cognos BI andImport and link a second data source Define a report drill through Framework Manager workflow processesRun scripts to automate or update a model Define a package-based drill through Verify relationships and query itemView lineage Identify drill-through values propertiesCreate a model report Advanced Generated SQL Concepts and Describe multi-fact queries and when fullOptimize and Tune Framework Manager Complex Queries outer joins are appropriateModels Stitch query SQL Identify the advantages of modelingWork in a Multi-Modeler Environment Conformed and non-conformed metadata as a star schemaSegment and link a project dimensions in generated SQL Create virtual facts to simplify writingBranch a project and merge results Multi-fact/multi-grain stitch query SQL queriesManage OLAP Data Sources Variances in Report Studio generated Use calculations to createPublish an OLAP model SQL commonly-needed query items for authorsPublish a model with multiple OLAP data Dimensionally modeled relational SQL Make time-based queries simple to authorsources generation by implementing a time dimensionPublish a model with an OLAP data source Cross join SQL Use determinants to specify multiple levelsand a relational data source Various results sets for multi-fact queries of granularity and prevent double-countingManage Framework Manager Packages Use Advanced Parameterization Identify the dimensions associated with aControl model versioning Techniques in Framework Manger fact tableNest packages Leverage session, model, and custom Identify key differences and

parameters recommendations for using data source,Create prompt macros model, and stored procedure query

line Leverage macro functions associated subjectsDescribe IBM Cognos components with security Examine the IBM Cognos BI securityDescribe IBM Cognos architecture at a high Model Maintenance and Extensibility environmentlevel Remap metadata to another source Apply dimensional information to relationalDefine IBM Cognos groups and roles Import and link a second data source Metadata to enable OLAP-style queriesExplain how to extend IBM Cognos Run scripts to automate or update a Describe model types and data entitiesIdentify Common Data Structures model Identify conformed values between dataExamine relationships and cardinality View lineage sourcesIdentify different data traps Create a model report Governors that affect SQL generationExamine OLAP data sources Optimize and Tune Framework Manager Identify session and model parametersGather Requirements Models Perform basic maintenance andDefine reporting requirements Work in a Multi-Modeler Environment management on a modelExplore data sources to identify data access Segment and link a project Identify and implement techniques tostrategies Branch a project and merge results optimize and tune your FrameworkCreate a Baseline Project Manage OLAP Data Sources Manager modelsDefine a project and its structure Publish an OLAP model Implement repository controlDescribe the Framework Manager Publish a model with multiple OLAP data Connect to an OLAP data source (cube) inenvironment sources a Framework Manager projectCreate a baseline project Publish a model with an OLAP data Specify package languages and functionEnhance the model with additional metadata source and a relational data source setsPrepare Reusable Metadata Manage Framework Manager PackagesEnsure efficient filters by configuring prompt Control model versioningproperties Nest packages lineModel for Predictable Results: Identify Describe IBM Cognos componentsReporting Issues Describe IBM Cognos architecture at aDescribe how IBM Cognos BI uses line high levelcardinality Discuss IBM Cognos and Performance Define IBM Cognos groups and rolesIdentify reporting traps Management Explain how to extend IBM CognosUse tools to analyze the model Examine the characteristics of Identify Common Data StructuresModel for Predictable Results: Virtual Star operational databases and databases Examine relationships and cardinalitySchemas designed for reporting Identify different data trapsModel in layers Examine key modeling recommendations Examine OLAP data sourcesCreate aliases to avoid ambiguous joins Examine the IBM Cognos BI and Gather RequirementsMerge query subjects to create as view Framework Manager workflow processes Define reporting requirementsbehavior Verify relationships and query item Explore data sources to identify data


Model for Predictable Results: Consolidate properties access strategiesMetadata Describe multi-fact queries and when full Create a Baseline ProjectCreate virtual dimensions to resolve outer joins are appropriate Define a project and its structurefact-to-fact joins Identify the advantages of modeling Describe the Framework ManagerCreate a consolidated modeling layer for metadata as a star schema environmentpresentation purposes Create virtual facts to simplify writing Create a baseline projectConsolidate snowflake dimensions with queries Enhance the model with additionalmodel query subjects Use calculations to create metadataSimplify facts by hiding unnecessary codes commonly-needed query items for Prepare Reusable MetadataCalculations and Filters authors Ensure efficient filters by configuringUse static filters to reduce the data returned Make time-based queries simple to prompt propertiesUse macros and parameters in calculations author by implementing a time dimension Model for Predictable Results: Identifyand filters to dynamically control the data Use determinants to specify multiple Reporting Issuesreturned levels of granularity and prevent Describe how IBM Cognos BI usesImplement a Time Dimension double-counting cardinalityResolve confusion caused by multiple Identify the dimensions associated with a Identify reporting trapsrelationships between a time dimension and fact table Use tools to analyze the modelanother table Identify key differences and Model for Predictable Results: Virtual StarSpecify Determinants recommendations for using data source, SchemasCreate the Presentation View model, and stored procedure query Model in layersIdentify conformed vs. non-conformed subjects Create aliases to avoid ambiguous joinsdimensions Examine the IBM Cognos BI security Merge query subjects to create as viewCreate star schema groupings to provide environment behaviorauthors with logical groupings of query Apply dimensional information to Model for Predictable Results: Consolidatesubjects relational Metadata to enable OLAP-style MetadataWork with Different Query Subject Types queries Create virtual dimensions to resolveIdentify the effects on generated SQL when Describe model types and data entities fact-to-fact joinsmodifying query subjects, SQL settings and Identify conformed values between data Create a consolidated modeling layer forrelationships sources presentation purposesSet Security in Framework Manager Governors that affect SQL generation Consolidate snowflake dimensions withRestrict access to packages Identify session and model parameters model query subjectsCreate and apply security filters Perform basic maintenance and Simplify facts by hiding unnecessary codesRestrict access to objects in the model management on a model Calculations and FiltersCreate Analysis Objects Identify and implement techniques to Use static filters to reduce the dataSort members for presentation and optimize and tune your Framework returnedpredictability Manager models Use macros and parameters inManage MUNs in Framework Manager Implement repository control calculations and filters to dynamicallyDefine members and member unique names Connect to an OLAP data source (cube) control the data returnedIdentify changes that impact a MUN in a Framework Manager project Implement a Time DimensionModel for Drill Through in Framework Specify package languages and function Resolve confusion caused by multipleManager sets relationships between a time dimensionDefine a report drill through and another tableDefine a package-based drill through Specify DeterminantsIdentify drill-through values line Create the Presentation ViewAdvanced Generated SQL Concepts and Describe IBM Cognos components Identify conformed vs. non-conformedComplex Queries Describe IBM Cognos architecture at a dimensionsStitch query SQL high level Create star schema groupings to provideConformed and non-conformed dimensions Define IBM Cognos groups and roles authors with logical groupings of queryin generated SQL Explain how to extend IBM Cognos subjectsMulti-fact/multi-grain stitch query SQL Identify Common Data Structures Work with Different Query Subject TypesVariances in Report Studio generated SQL Examine relationships and cardinality Identify the effects on generated SQLDimensionally modeled relational SQL Identify different data traps when modifying query subjects, SQLgeneration Examine OLAP data sources settings and relationshipsCross join SQL Gather Requirements Set Security in Framework ManagerVarious results sets for multi-fact queries Define reporting requirements Restrict access to packagesUse Advanced Parameterization Techniques Explore data sources to identify data Create and apply security filtersin Framework Manger access strategies Restrict access to objects in the modelLeverage session, model, and custom Create a Baseline Project Create Analysis Objectsparameters Define a project and its structure Sort members for presentation andCreate prompt macros Describe the Framework Manager predictabilityLeverage macro functions associated with environment Manage MUNs in Framework Managersecurity Create a baseline project Define members and member uniqueModel Maintenance and Extensibility Enhance the model with additional namesRemap metadata to another source metadata Identify changes that impact a MUNImport and link a second data source Prepare Reusable Metadata Model for Drill Through in FrameworkRun scripts to automate or update a model Ensure efficient filters by configuring Manager


View lineage prompt properties Define a report drill throughCreate a model report Model for Predictable Results: Identify Define a package-based drill throughOptimize and Tune Framework Manager Reporting Issues Identify drill-through valuesModels Describe how IBM Cognos BI uses Advanced Generated SQL Concepts andWork in a Multi-Modeler Environment cardinality Complex QueriesSegment and link a project Identify reporting traps Stitch query SQLBranch a project and merge results Use tools to analyze the model Conformed and non-conformedManage OLAP Data Sources Model for Predictable Results: Virtual dimensions in generated SQLPublish an OLAP model Star Schemas Multi-fact/multi-grain stitch query SQLPublish a model with multiple OLAP data Model in layers Variances in Report Studio generated SQLsources Create aliases to avoid ambiguous joins Dimensionally modeled relational SQLPublish a model with an OLAP data source Merge query subjects to create as view generationand a relational data source behavior Cross join SQLManage Framework Manager Packages Model for Predictable Results: Various results sets for multi-fact queriesControl model versioning Consolidate Metadata Use Advanced ParameterizationNest packages Create virtual dimensions to resolve Techniques in Framework Manger

fact-to-fact joins Leverage session, model, and customCreate a consolidated modeling layer for parameters

line presentation purposes Create prompt macrosDescribe IBM Cognos components Consolidate snowflake dimensions with Leverage macro functions associated withDescribe IBM Cognos architecture at a high model query subjects securitylevel Simplify facts by hiding unnecessary Model Maintenance and ExtensibilityDefine IBM Cognos groups and roles codes Remap metadata to another sourceExplain how to extend IBM Cognos Calculations and Filters Import and link a second data sourceIdentify Common Data Structures Use static filters to reduce the data Run scripts to automate or update a modelExamine relationships and cardinality returned View lineageIdentify different data traps Use macros and parameters in Create a model reportExamine OLAP data sources calculations and filters to dynamically Optimize and Tune Framework ManagerGather Requirements control the data returned ModelsDefine reporting requirements Implement a Time Dimension Work in a Multi-Modeler EnvironmentExplore data sources to identify data access Resolve confusion caused by multiple Segment and link a projectstrategies relationships between a time dimension Branch a project and merge resultsCreate a Baseline Project and another table Manage OLAP Data SourcesDefine a project and its structure Specify Determinants Publish an OLAP modelDescribe the Framework Manager Create the Presentation View Publish a model with multiple OLAP dataenvironment Identify conformed vs. non-conformed sourcesCreate a baseline project dimensions Publish a model with an OLAP data sourceEnhance the model with additional metadata Create star schema groupings to provide and a relational data sourcePrepare Reusable Metadata authors with logical groupings of query Manage Framework Manager PackagesEnsure efficient filters by configuring prompt subjects Control model versioningproperties Work with Different Query Subject Types Nest packagesModel for Predictable Results: Identify Identify the effects on generated SQLReporting Issues when modifying query subjects, SQLDescribe how IBM Cognos BI uses settings and relationships linecardinality Set Security in Framework Manager Describe IBM Cognos componentsIdentify reporting traps Restrict access to packages Describe IBM Cognos architecture at aUse tools to analyze the model Create and apply security filters high levelModel for Predictable Results: Virtual Star Restrict access to objects in the model Define IBM Cognos groups and rolesSchemas Create Analysis Objects Explain how to extend IBM CognosModel in layers Sort members for presentation and Identify Common Data StructuresCreate aliases to avoid ambiguous joins predictability Examine relationships and cardinalityMerge query subjects to create as view Manage MUNs in Framework Manager Identify different data trapsbehavior Define members and member unique Examine OLAP data sourcesModel for Predictable Results: Consolidate names Gather RequirementsMetadata Identify changes that impact a MUN Define reporting requirementsCreate virtual dimensions to resolve Model for Drill Through in Framework Explore data sources to identify datafact-to-fact joins Manager access strategiesCreate a consolidated modeling layer for Define a report drill through Create a Baseline Projectpresentation purposes Define a package-based drill through Define a project and its structureConsolidate snowflake dimensions with Identify drill-through values Describe the Framework Managermodel query subjects Advanced Generated SQL Concepts and environmentSimplify facts by hiding unnecessary codes Complex Queries Create a baseline projectCalculations and Filters Stitch query SQL Enhance the model with additionalUse static filters to reduce the data returned Conformed and non-conformed metadataUse macros and parameters in calculations dimensions in generated SQL Prepare Reusable Metadataand filters to dynamically control the data Multi-fact/multi-grain stitch query SQL Ensure efficient filters by configuring


returned Variances in Report Studio generated prompt propertiesImplement a Time Dimension SQL Model for Predictable Results: IdentifyResolve confusion caused by multiple Dimensionally modeled relational SQL Reporting Issuesrelationships between a time dimension and generation Describe how IBM Cognos BI usesanother table Cross join SQL cardinalitySpecify Determinants Various results sets for multi-fact queries Identify reporting trapsCreate the Presentation View Use Advanced Parameterization Use tools to analyze the modelIdentify conformed vs. non-conformed Techniques in Framework Manger Model for Predictable Results: Virtual Stardimensions Leverage session, model, and custom SchemasCreate star schema groupings to provide parameters Model in layersauthors with logical groupings of query Create prompt macros Create aliases to avoid ambiguous joinssubjects Leverage macro functions associated Merge query subjects to create as viewWork with Different Query Subject Types with security behaviorIdentify the effects on generated SQL when Model Maintenance and Extensibility Model for Predictable Results: Consolidatemodifying query subjects, SQL settings and Remap metadata to another source Metadatarelationships Import and link a second data source Create virtual dimensions to resolveSet Security in Framework Manager Run scripts to automate or update a fact-to-fact joinsRestrict access to packages model Create a consolidated modeling layer forCreate and apply security filters View lineage presentation purposesRestrict access to objects in the model Create a model report Consolidate snowflake dimensions withCreate Analysis Objects Optimize and Tune Framework Manager model query subjectsSort members for presentation and Models Simplify facts by hiding unnecessary codespredictability Work in a Multi-Modeler Environment Calculations and FiltersManage MUNs in Framework Manager Segment and link a project Use static filters to reduce the dataDefine members and member unique names Branch a project and merge results returnedIdentify changes that impact a MUN Manage OLAP Data Sources Use macros and parameters inModel for Drill Through in Framework Publish an OLAP model calculations and filters to dynamicallyManager Publish a model with multiple OLAP data control the data returnedDefine a report drill through sources Implement a Time DimensionDefine a package-based drill through Publish a model with an OLAP data Resolve confusion caused by multipleIdentify drill-through values source and a relational data source relationships between a time dimensionAdvanced Generated SQL Concepts and Manage Framework Manager Packages and another tableComplex Queries Control model versioning Specify DeterminantsStitch query SQL Nest packages Create the Presentation ViewConformed and non-conformed dimensions Identify conformed vs. non-conformedin generated SQL dimensionsMulti-fact/multi-grain stitch query SQL line Create star schema groupings to provideVariances in Report Studio generated SQL Describe IBM Cognos components authors with logical groupings of queryDimensionally modeled relational SQL Describe IBM Cognos architecture at a subjectsgeneration high level Work with Different Query Subject TypesCross join SQL Define IBM Cognos groups and roles Identify the effects on generated SQLVarious results sets for multi-fact queries Explain how to extend IBM Cognos when modifying query subjects, SQLUse Advanced Parameterization Techniques Identify Common Data Structures settings and relationshipsin Framework Manger Examine relationships and cardinality Set Security in Framework ManagerLeverage session, model, and custom Identify different data traps Restrict access to packagesparameters Examine OLAP data sources Create and apply security filtersCreate prompt macros Gather Requirements Restrict access to objects in the modelLeverage macro functions associated with Define reporting requirements Create Analysis Objectssecurity Explore data sources to identify data Sort members for presentation andModel Maintenance and Extensibility access strategies predictabilityRemap metadata to another source Create a Baseline Project Manage MUNs in Framework ManagerImport and link a second data source Define a project and its structure Define members and member uniqueRun scripts to automate or update a model Describe the Framework Manager namesView lineage environment Identify changes that impact a MUNCreate a model report Create a baseline project Model for Drill Through in FrameworkOptimize and Tune Framework Manager Enhance the model with additional ManagerModels metadata Define a report drill throughWork in a Multi-Modeler Environment Prepare Reusable Metadata Define a package-based drill throughSegment and link a project Ensure efficient filters by configuring Identify drill-through valuesBranch a project and merge results prompt properties Advanced Generated SQL Concepts andManage OLAP Data Sources Model for Predictable Results: Identify Complex QueriesPublish an OLAP model Reporting Issues Stitch query SQLPublish a model with multiple OLAP data Describe how IBM Cognos BI uses Conformed and non-conformedsources cardinality dimensions in generated SQLPublish a model with an OLAP data source Identify reporting traps Multi-fact/multi-grain stitch query SQLand a relational data source Use tools to analyze the model Variances in Report Studio generated SQL


Manage Framework Manager Packages Model for Predictable Results: Virtual Dimensionally modeled relational SQLControl model versioning Star Schemas generationNest packages Model in layers Cross join SQL

Create aliases to avoid ambiguous joins Various results sets for multi-fact queriesMerge query subjects to create as view Use Advanced Parameterization

line behavior Techniques in Framework MangerDescribe IBM Cognos components Model for Predictable Results: Leverage session, model, and customDescribe IBM Cognos architecture at a high Consolidate Metadata parameterslevel Create virtual dimensions to resolve Create prompt macrosDefine IBM Cognos groups and roles fact-to-fact joins Leverage macro functions associated withExplain how to extend IBM Cognos Create a consolidated modeling layer for securityIdentify Common Data Structures presentation purposes Model Maintenance and ExtensibilityExamine relationships and cardinality Consolidate snowflake dimensions with Remap metadata to another sourceIdentify different data traps model query subjects Import and link a second data sourceExamine OLAP data sources Simplify facts by hiding unnecessary Run scripts to automate or update a modelGather Requirements codes View lineageDefine reporting requirements Calculations and Filters Create a model reportExplore data sources to identify data access Use static filters to reduce the data Optimize and Tune Framework Managerstrategies returned ModelsCreate a Baseline Project Use macros and parameters in Work in a Multi-Modeler EnvironmentDefine a project and its structure calculations and filters to dynamically Segment and link a projectDescribe the Framework Manager control the data returned Branch a project and merge resultsenvironment Implement a Time Dimension Manage OLAP Data SourcesCreate a baseline project Resolve confusion caused by multiple Publish an OLAP modelEnhance the model with additional metadata relationships between a time dimension Publish a model with multiple OLAP dataPrepare Reusable Metadata and another table sourcesEnsure efficient filters by configuring prompt Specify Determinants Publish a model with an OLAP data sourceproperties Create the Presentation View and a relational data sourceModel for Predictable Results: Identify Identify conformed vs. non-conformed Manage Framework Manager PackagesReporting Issues dimensions Control model versioningDescribe how IBM Cognos BI uses Create star schema groupings to provide Nest packagescardinality authors with logical groupings of queryIdentify reporting traps subjectsUse tools to analyze the model Work with Different Query Subject Types lineModel for Predictable Results: Virtual Star Identify the effects on generated SQL Describe IBM Cognos componentsSchemas when modifying query subjects, SQL Describe IBM Cognos architecture at aModel in layers settings and relationships high levelCreate aliases to avoid ambiguous joins Set Security in Framework Manager Define IBM Cognos groups and rolesMerge query subjects to create as view Restrict access to packages Explain how to extend IBM Cognosbehavior Create and apply security filters Identify Common Data StructuresModel for Predictable Results: Consolidate Restrict access to objects in the model Examine relationships and cardinalityMetadata Create Analysis Objects Identify different data trapsCreate virtual dimensions to resolve Sort members for presentation and Examine OLAP data sourcesfact-to-fact joins predictability Gather RequirementsCreate a consolidated modeling layer for Manage MUNs in Framework Manager Define reporting requirementspresentation purposes Define members and member unique Explore data sources to identify dataConsolidate snowflake dimensions with names access strategiesmodel query subjects Identify changes that impact a MUN Create a Baseline ProjectSimplify facts by hiding unnecessary codes Model for Drill Through in Framework Define a project and its structureCalculations and Filters Manager Describe the Framework ManagerUse static filters to reduce the data returned Define a report drill through environmentUse macros and parameters in calculations Define a package-based drill through Create a baseline projectand filters to dynamically control the data Identify drill-through values Enhance the model with additionalreturned Advanced Generated SQL Concepts and metadataImplement a Time Dimension Complex Queries Prepare Reusable MetadataResolve confusion caused by multiple Stitch query SQL Ensure efficient filters by configuringrelationships between a time dimension and Conformed and non-conformed prompt propertiesanother table dimensions in generated SQL Model for Predictable Results: IdentifySpecify Determinants Multi-fact/multi-grain stitch query SQL Reporting IssuesCreate the Presentation View Variances in Report Studio generated Describe how IBM Cognos BI usesIdentify conformed vs. non-conformed SQL cardinalitydimensions Dimensionally modeled relational SQL Identify reporting trapsCreate star schema groupings to provide generation Use tools to analyze the modelauthors with logical groupings of query Cross join SQL Model for Predictable Results: Virtual Starsubjects Various results sets for multi-fact queries SchemasWork with Different Query Subject Types Use Advanced Parameterization Model in layers


Identify the effects on generated SQL when Techniques in Framework Manger Create aliases to avoid ambiguous joinsmodifying query subjects, SQL settings and Leverage session, model, and custom Merge query subjects to create as viewrelationships parameters behaviorSet Security in Framework Manager Create prompt macros Model for Predictable Results: ConsolidateRestrict access to packages Leverage macro functions associated MetadataCreate and apply security filters with security Create virtual dimensions to resolveRestrict access to objects in the model Model Maintenance and Extensibility fact-to-fact joinsCreate Analysis Objects Remap metadata to another source Create a consolidated modeling layer forSort members for presentation and Import and link a second data source presentation purposespredictability Run scripts to automate or update a Consolidate snowflake dimensions withManage MUNs in Framework Manager model model query subjectsDefine members and member unique names View lineage Simplify facts by hiding unnecessary codesIdentify changes that impact a MUN Create a model report Calculations and FiltersModel for Drill Through in Framework Optimize and Tune Framework Manager Use static filters to reduce the dataManager Models returnedDefine a report drill through Work in a Multi-Modeler Environment Use macros and parameters inDefine a package-based drill through Segment and link a project calculations and filters to dynamicallyIdentify drill-through values Branch a project and merge results control the data returnedAdvanced Generated SQL Concepts and Manage OLAP Data Sources Implement a Time DimensionComplex Queries Publish an OLAP model Resolve confusion caused by multipleStitch query SQL Publish a model with multiple OLAP data relationships between a time dimensionConformed and non-conformed dimensions sources and another tablein generated SQL Publish a model with an OLAP data Specify DeterminantsMulti-fact/multi-grain stitch query SQL source and a relational data source Create the Presentation ViewVariances in Report Studio generated SQL Manage Framework Manager Packages Identify conformed vs. non-conformedDimensionally modeled relational SQL Control model versioning dimensionsgeneration Nest packages Create star schema groupings to provideCross join SQL authors with logical groupings of queryVarious results sets for multi-fact queries subjectsUse Advanced Parameterization Techniques line Work with Different Query Subject Typesin Framework Manger Discuss IBM Cognos and Performance Identify the effects on generated SQLLeverage session, model, and custom Management when modifying query subjects, SQLparameters Examine the characteristics of settings and relationshipsCreate prompt macros operational databases and databases Set Security in Framework ManagerLeverage macro functions associated with designed for reporting Restrict access to packagessecurity Examine key modeling recommendations Create and apply security filtersModel Maintenance and Extensibility Examine the IBM Cognos BI and Restrict access to objects in the modelRemap metadata to another source Framework Manager workflow processes Create Analysis ObjectsImport and link a second data source Verify relationships and query item Sort members for presentation andRun scripts to automate or update a model properties predictabilityView lineage Describe multi-fact queries and when full Manage MUNs in Framework ManagerCreate a model report outer joins are appropriate Define members and member uniqueOptimize and Tune Framework Manager Identify the advantages of modeling namesModels metadata as a star schema Identify changes that impact a MUNWork in a Multi-Modeler Environment Create virtual facts to simplify writing Model for Drill Through in FrameworkSegment and link a project queries ManagerBranch a project and merge results Use calculations to create Define a report drill throughManage OLAP Data Sources commonly-needed query items for Define a package-based drill throughPublish an OLAP model authors Identify drill-through valuesPublish a model with multiple OLAP data Make time-based queries simple to Advanced Generated SQL Concepts andsources author by implementing a time dimension Complex QueriesPublish a model with an OLAP data source Use determinants to specify multiple Stitch query SQLand a relational data source levels of granularity and prevent Conformed and non-conformedManage Framework Manager Packages double-counting dimensions in generated SQLControl model versioning Identify the dimensions associated with a Multi-fact/multi-grain stitch query SQLNest packages fact table Variances in Report Studio generated SQL

Identify key differences and Dimensionally modeled relational SQLrecommendations for using data source, generation

line model, and stored procedure query Cross join SQLDiscuss IBM Cognos and Performance subjects Various results sets for multi-fact queriesManagement Examine the IBM Cognos BI security Use Advanced ParameterizationExamine the characteristics of operational environment Techniques in Framework Mangerdatabases and databases designed for Apply dimensional information to Leverage session, model, and customreporting relational Metadata to enable OLAP-style parametersExamine key modeling recommendations queries Create prompt macrosExamine the IBM Cognos BI and Framework Describe model types and data entities Leverage macro functions associated with


Manager workflow processes Identify conformed values between data securityVerify relationships and query item sources Model Maintenance and Extensibilityproperties Governors that affect SQL generation Remap metadata to another sourceDescribe multi-fact queries and when full Identify session and model parameters Import and link a second data sourceouter joins are appropriate Perform basic maintenance and Run scripts to automate or update a modelIdentify the advantages of modeling management on a model View lineagemetadata as a star schema Identify and implement techniques to Create a model reportCreate virtual facts to simplify writing queries optimize and tune your Framework Optimize and Tune Framework ManagerUse calculations to create Manager models Modelscommonly-needed query items for authors Implement repository control Work in a Multi-Modeler EnvironmentMake time-based queries simple to author Connect to an OLAP data source (cube) Segment and link a projectby implementing a time dimension in a Framework Manager project Branch a project and merge resultsUse determinants to specify multiple levels Specify package languages and function Manage OLAP Data Sourcesof granularity and prevent double-counting sets Publish an OLAP modelIdentify the dimensions associated with a Publish a model with multiple OLAP datafact table sourcesIdentify key differences and line Publish a model with an OLAP data sourcerecommendations for using data source, Describe IBM Cognos components and a relational data sourcemodel, and stored procedure query subjects Describe IBM Cognos architecture at a Manage Framework Manager PackagesExamine the IBM Cognos BI security high level Control model versioningenvironment Define IBM Cognos groups and roles Nest packagesApply dimensional information to relational Explain how to extend IBM CognosMetadata to enable OLAP-style queries Identify Common Data StructuresDescribe model types and data entities Examine relationships and cardinality lineIdentify conformed values between data Identify different data traps Discuss IBM Cognos and Performancesources Examine OLAP data sources ManagementGovernors that affect SQL generation Gather Requirements Examine the characteristics of operationalIdentify session and model parameters Define reporting requirements databases and databases designed forPerform basic maintenance and Explore data sources to identify data reportingmanagement on a model access strategies Examine key modeling recommendationsIdentify and implement techniques to Create a Baseline Project Examine the IBM Cognos BI andoptimize and tune your Framework Manager Define a project and its structure Framework Manager workflow processesmodels Describe the Framework Manager Verify relationships and query itemImplement repository control environment propertiesConnect to an OLAP data source (cube) in a Create a baseline project Describe multi-fact queries and when fullFramework Manager project Enhance the model with additional outer joins are appropriateSpecify package languages and function metadata Identify the advantages of modelingsets Prepare Reusable Metadata metadata as a star schema

Ensure efficient filters by configuring Create virtual facts to simplify writingprompt properties queries

line Model for Predictable Results: Identify Use calculations to createDescribe IBM Cognos components Reporting Issues commonly-needed query items for authorsDescribe IBM Cognos architecture at a high Describe how IBM Cognos BI uses Make time-based queries simple to authorlevel cardinality by implementing a time dimensionDefine IBM Cognos groups and roles Identify reporting traps Use determinants to specify multiple levelsExplain how to extend IBM Cognos Use tools to analyze the model of granularity and prevent double-countingIdentify Common Data Structures Model for Predictable Results: Virtual Identify the dimensions associated with aExamine relationships and cardinality Star Schemas fact tableIdentify different data traps Model in layers Identify key differences andExamine OLAP data sources Create aliases to avoid ambiguous joins recommendations for using data source,Gather Requirements Merge query subjects to create as view model, and stored procedure queryDefine reporting requirements behavior subjectsExplore data sources to identify data access Model for Predictable Results: Examine the IBM Cognos BI securitystrategies Consolidate Metadata environmentCreate a Baseline Project Create virtual dimensions to resolve Apply dimensional information to relationalDefine a project and its structure fact-to-fact joins Metadata to enable OLAP-style queriesDescribe the Framework Manager Create a consolidated modeling layer for Describe model types and data entitiesenvironment presentation purposes Identify conformed values between dataCreate a baseline project Consolidate snowflake dimensions with sourcesEnhance the model with additional metadata model query subjects Governors that affect SQL generationPrepare Reusable Metadata Simplify facts by hiding unnecessary Identify session and model parametersEnsure efficient filters by configuring prompt codes Perform basic maintenance andproperties Calculations and Filters management on a modelModel for Predictable Results: Identify Use static filters to reduce the data Identify and implement techniques toReporting Issues returned optimize and tune your FrameworkDescribe how IBM Cognos BI uses Use macros and parameters in Manager models


cardinality calculations and filters to dynamically Implement repository controlIdentify reporting traps control the data returned Connect to an OLAP data source (cube) inUse tools to analyze the model Implement a Time Dimension a Framework Manager projectModel for Predictable Results: Virtual Star Resolve confusion caused by multiple Specify package languages and functionSchemas relationships between a time dimension setsModel in layers and another tableCreate aliases to avoid ambiguous joins Specify DeterminantsMerge query subjects to create as view Create the Presentation View linebehavior Identify conformed vs. non-conformed Describe IBM Cognos componentsModel for Predictable Results: Consolidate dimensions Describe IBM Cognos architecture at aMetadata Create star schema groupings to provide high levelCreate virtual dimensions to resolve authors with logical groupings of query Define IBM Cognos groups and rolesfact-to-fact joins subjects Explain how to extend IBM CognosCreate a consolidated modeling layer for Work with Different Query Subject Types Identify Common Data Structurespresentation purposes Identify the effects on generated SQL Examine relationships and cardinalityConsolidate snowflake dimensions with when modifying query subjects, SQL Identify different data trapsmodel query subjects settings and relationships Examine OLAP data sourcesSimplify facts by hiding unnecessary codes Set Security in Framework Manager Gather RequirementsCalculations and Filters Restrict access to packages Define reporting requirementsUse static filters to reduce the data returned Create and apply security filters Explore data sources to identify dataUse macros and parameters in calculations Restrict access to objects in the model access strategiesand filters to dynamically control the data Create Analysis Objects Create a Baseline Projectreturned Sort members for presentation and Define a project and its structureImplement a Time Dimension predictability Describe the Framework ManagerResolve confusion caused by multiple Manage MUNs in Framework Manager environmentrelationships between a time dimension and Define members and member unique Create a baseline projectanother table names Enhance the model with additionalSpecify Determinants Identify changes that impact a MUN metadataCreate the Presentation View Model for Drill Through in Framework Prepare Reusable MetadataIdentify conformed vs. non-conformed Manager Ensure efficient filters by configuringdimensions Define a report drill through prompt propertiesCreate star schema groupings to provide Define a package-based drill through Model for Predictable Results: Identifyauthors with logical groupings of query Identify drill-through values Reporting Issuessubjects Advanced Generated SQL Concepts and Describe how IBM Cognos BI usesWork with Different Query Subject Types Complex Queries cardinalityIdentify the effects on generated SQL when Stitch query SQL Identify reporting trapsmodifying query subjects, SQL settings and Conformed and non-conformed Use tools to analyze the modelrelationships dimensions in generated SQL Model for Predictable Results: Virtual StarSet Security in Framework Manager Multi-fact/multi-grain stitch query SQL SchemasRestrict access to packages Variances in Report Studio generated Model in layersCreate and apply security filters SQL Create aliases to avoid ambiguous joinsRestrict access to objects in the model Dimensionally modeled relational SQL Merge query subjects to create as viewCreate Analysis Objects generation behaviorSort members for presentation and Cross join SQL Model for Predictable Results: Consolidatepredictability Various results sets for multi-fact queries MetadataManage MUNs in Framework Manager Use Advanced Parameterization Create virtual dimensions to resolveDefine members and member unique names Techniques in Framework Manger fact-to-fact joinsIdentify changes that impact a MUN Leverage session, model, and custom Create a consolidated modeling layer forModel for Drill Through in Framework parameters presentation purposesManager Create prompt macros Consolidate snowflake dimensions withDefine a report drill through Leverage macro functions associated model query subjectsDefine a package-based drill through with security Simplify facts by hiding unnecessary codesIdentify drill-through values Model Maintenance and Extensibility Calculations and FiltersAdvanced Generated SQL Concepts and Remap metadata to another source Use static filters to reduce the dataComplex Queries Import and link a second data source returnedStitch query SQL Run scripts to automate or update a Use macros and parameters inConformed and non-conformed dimensions model calculations and filters to dynamicallyin generated SQL View lineage control the data returnedMulti-fact/multi-grain stitch query SQL Create a model report Implement a Time DimensionVariances in Report Studio generated SQL Optimize and Tune Framework Manager Resolve confusion caused by multipleDimensionally modeled relational SQL Models relationships between a time dimensiongeneration Work in a Multi-Modeler Environment and another tableCross join SQL Segment and link a project Specify DeterminantsVarious results sets for multi-fact queries Branch a project and merge results Create the Presentation ViewUse Advanced Parameterization Techniques Manage OLAP Data Sources Identify conformed vs. non-conformedin Framework Manger Publish an OLAP model dimensions


Leverage session, model, and custom Publish a model with multiple OLAP data Create star schema groupings to provideparameters sources authors with logical groupings of queryCreate prompt macros Publish a model with an OLAP data subjectsLeverage macro functions associated with source and a relational data source Work with Different Query Subject Typessecurity Manage Framework Manager Packages Identify the effects on generated SQLModel Maintenance and Extensibility Control model versioning when modifying query subjects, SQLRemap metadata to another source Nest packages settings and relationshipsImport and link a second data source Set Security in Framework ManagerRun scripts to automate or update a model Restrict access to packagesView lineage line Create and apply security filtersCreate a model report Describe IBM Cognos components Restrict access to objects in the modelOptimize and Tune Framework Manager Describe IBM Cognos architecture at a Create Analysis ObjectsModels high level Sort members for presentation andWork in a Multi-Modeler Environment Define IBM Cognos groups and roles predictabilitySegment and link a project Explain how to extend IBM Cognos Manage MUNs in Framework ManagerBranch a project and merge results Identify Common Data Structures Define members and member uniqueManage OLAP Data Sources Examine relationships and cardinality namesPublish an OLAP model Identify different data traps Identify changes that impact a MUNPublish a model with multiple OLAP data Examine OLAP data sources Model for Drill Through in Frameworksources Gather Requirements ManagerPublish a model with an OLAP data source Define reporting requirements Define a report drill throughand a relational data source Explore data sources to identify data Define a package-based drill throughManage Framework Manager Packages access strategies Identify drill-through valuesControl model versioning Create a Baseline Project Advanced Generated SQL Concepts andNest packages Define a project and its structure Complex Queries

Describe the Framework Manager Stitch query SQLenvironment Conformed and non-conformed

line Create a baseline project dimensions in generated SQLDescribe IBM Cognos components Enhance the model with additional Multi-fact/multi-grain stitch query SQLDescribe IBM Cognos architecture at a high metadata Variances in Report Studio generated SQLlevel Prepare Reusable Metadata Dimensionally modeled relational SQLDefine IBM Cognos groups and roles Ensure efficient filters by configuring generationExplain how to extend IBM Cognos prompt properties Cross join SQLIdentify Common Data Structures Model for Predictable Results: Identify Various results sets for multi-fact queriesExamine relationships and cardinality Reporting Issues Use Advanced ParameterizationIdentify different data traps Describe how IBM Cognos BI uses Techniques in Framework MangerExamine OLAP data sources cardinality Leverage session, model, and customGather Requirements Identify reporting traps parametersDefine reporting requirements Use tools to analyze the model Create prompt macrosExplore data sources to identify data access Model for Predictable Results: Virtual Leverage macro functions associated withstrategies Star Schemas securityCreate a Baseline Project Model in layers Model Maintenance and ExtensibilityDefine a project and its structure Create aliases to avoid ambiguous joins Remap metadata to another sourceDescribe the Framework Manager Merge query subjects to create as view Import and link a second data sourceenvironment behavior Run scripts to automate or update a modelCreate a baseline project Model for Predictable Results: View lineageEnhance the model with additional metadata Consolidate Metadata Create a model reportPrepare Reusable Metadata Create virtual dimensions to resolve Optimize and Tune Framework ManagerEnsure efficient filters by configuring prompt fact-to-fact joins Modelsproperties Create a consolidated modeling layer for Work in a Multi-Modeler EnvironmentModel for Predictable Results: Identify presentation purposes Segment and link a projectReporting Issues Consolidate snowflake dimensions with Branch a project and merge resultsDescribe how IBM Cognos BI uses model query subjects Manage OLAP Data Sourcescardinality Simplify facts by hiding unnecessary Publish an OLAP modelIdentify reporting traps codes Publish a model with multiple OLAP dataUse tools to analyze the model Calculations and Filters sourcesModel for Predictable Results: Virtual Star Use static filters to reduce the data Publish a model with an OLAP data sourceSchemas returned and a relational data sourceModel in layers Use macros and parameters in Manage Framework Manager PackagesCreate aliases to avoid ambiguous joins calculations and filters to dynamically Control model versioningMerge query subjects to create as view control the data returned Nest packagesbehavior Implement a Time DimensionModel for Predictable Results: Consolidate Resolve confusion caused by multipleMetadata relationships between a time dimension lineCreate virtual dimensions to resolve and another table Describe IBM Cognos componentsfact-to-fact joins Specify Determinants Describe IBM Cognos architecture at a


Create a consolidated modeling layer for Create the Presentation View high levelpresentation purposes Identify conformed vs. non-conformed Define IBM Cognos groups and rolesConsolidate snowflake dimensions with dimensions Explain how to extend IBM Cognosmodel query subjects Create star schema groupings to provide Identify Common Data StructuresSimplify facts by hiding unnecessary codes authors with logical groupings of query Examine relationships and cardinalityCalculations and Filters subjects Identify different data trapsUse static filters to reduce the data returned Work with Different Query Subject Types Examine OLAP data sourcesUse macros and parameters in calculations Identify the effects on generated SQL Gather Requirementsand filters to dynamically control the data when modifying query subjects, SQL Define reporting requirementsreturned settings and relationships Explore data sources to identify dataImplement a Time Dimension Set Security in Framework Manager access strategiesResolve confusion caused by multiple Restrict access to packages Create a Baseline Projectrelationships between a time dimension and Create and apply security filters Define a project and its structureanother table Restrict access to objects in the model Describe the Framework ManagerSpecify Determinants Create Analysis Objects environmentCreate the Presentation View Sort members for presentation and Create a baseline projectIdentify conformed vs. non-conformed predictability Enhance the model with additionaldimensions Manage MUNs in Framework Manager metadataCreate star schema groupings to provide Define members and member unique Prepare Reusable Metadataauthors with logical groupings of query names Ensure efficient filters by configuringsubjects Identify changes that impact a MUN prompt propertiesWork with Different Query Subject Types Model for Drill Through in Framework Model for Predictable Results: IdentifyIdentify the effects on generated SQL when Manager Reporting Issuesmodifying query subjects, SQL settings and Define a report drill through Describe how IBM Cognos BI usesrelationships Define a package-based drill through cardinalitySet Security in Framework Manager Identify drill-through values Identify reporting trapsRestrict access to packages Advanced Generated SQL Concepts and Use tools to analyze the modelCreate and apply security filters Complex Queries Model for Predictable Results: Virtual StarRestrict access to objects in the model Stitch query SQL SchemasCreate Analysis Objects Conformed and non-conformed Model in layersSort members for presentation and dimensions in generated SQL Create aliases to avoid ambiguous joinspredictability Multi-fact/multi-grain stitch query SQL Merge query subjects to create as viewManage MUNs in Framework Manager Variances in Report Studio generated behaviorDefine members and member unique names SQL Model for Predictable Results: ConsolidateIdentify changes that impact a MUN Dimensionally modeled relational SQL MetadataModel for Drill Through in Framework generation Create virtual dimensions to resolveManager Cross join SQL fact-to-fact joinsDefine a report drill through Various results sets for multi-fact queries Create a consolidated modeling layer forDefine a package-based drill through Use Advanced Parameterization presentation purposesIdentify drill-through values Techniques in Framework Manger Consolidate snowflake dimensions withAdvanced Generated SQL Concepts and Leverage session, model, and custom model query subjectsComplex Queries parameters Simplify facts by hiding unnecessary codesStitch query SQL Create prompt macros Calculations and FiltersConformed and non-conformed dimensions Leverage macro functions associated Use static filters to reduce the datain generated SQL with security returnedMulti-fact/multi-grain stitch query SQL Model Maintenance and Extensibility Use macros and parameters inVariances in Report Studio generated SQL Remap metadata to another source calculations and filters to dynamicallyDimensionally modeled relational SQL Import and link a second data source control the data returnedgeneration Run scripts to automate or update a Implement a Time DimensionCross join SQL model Resolve confusion caused by multipleVarious results sets for multi-fact queries View lineage relationships between a time dimensionUse Advanced Parameterization Techniques Create a model report and another tablein Framework Manger Optimize and Tune Framework Manager Specify DeterminantsLeverage session, model, and custom Models Create the Presentation Viewparameters Work in a Multi-Modeler Environment Identify conformed vs. non-conformedCreate prompt macros Segment and link a project dimensionsLeverage macro functions associated with Branch a project and merge results Create star schema groupings to providesecurity Manage OLAP Data Sources authors with logical groupings of queryModel Maintenance and Extensibility Publish an OLAP model subjectsRemap metadata to another source Publish a model with multiple OLAP data Work with Different Query Subject TypesImport and link a second data source sources Identify the effects on generated SQLRun scripts to automate or update a model Publish a model with an OLAP data when modifying query subjects, SQLView lineage source and a relational data source settings and relationshipsCreate a model report Manage Framework Manager Packages Set Security in Framework ManagerOptimize and Tune Framework Manager Control model versioning Restrict access to packagesModels Nest packages Create and apply security filters


Work in a Multi-Modeler Environment Restrict access to objects in the modelSegment and link a project Create Analysis ObjectsBranch a project and merge results line Sort members for presentation andManage OLAP Data Sources Describe IBM Cognos components predictabilityPublish an OLAP model Describe IBM Cognos architecture at a Manage MUNs in Framework ManagerPublish a model with multiple OLAP data high level Define members and member uniquesources Define IBM Cognos groups and roles namesPublish a model with an OLAP data source Explain how to extend IBM Cognos Identify changes that impact a MUNand a relational data source Identify Common Data Structures Model for Drill Through in FrameworkManage Framework Manager Packages Examine relationships and cardinality ManagerControl model versioning Identify different data traps Define a report drill throughNest packages Examine OLAP data sources Define a package-based drill through

Gather Requirements Identify drill-through valuesDefine reporting requirements Advanced Generated SQL Concepts and

line Explore data sources to identify data Complex QueriesDescribe IBM Cognos components access strategies Stitch query SQLDescribe IBM Cognos architecture at a high Create a Baseline Project Conformed and non-conformedlevel Define a project and its structure dimensions in generated SQLDefine IBM Cognos groups and roles Describe the Framework Manager Multi-fact/multi-grain stitch query SQLExplain how to extend IBM Cognos environment Variances in Report Studio generated SQLIdentify Common Data Structures Create a baseline project Dimensionally modeled relational SQLExamine relationships and cardinality Enhance the model with additional generationIdentify different data traps metadata Cross join SQLExamine OLAP data sources Prepare Reusable Metadata Various results sets for multi-fact queriesGather Requirements Ensure efficient filters by configuring Use Advanced ParameterizationDefine reporting requirements prompt properties Techniques in Framework MangerExplore data sources to identify data access Model for Predictable Results: Identify Leverage session, model, and customstrategies Reporting Issues parametersCreate a Baseline Project Describe how IBM Cognos BI uses Create prompt macrosDefine a project and its structure cardinality Leverage macro functions associated withDescribe the Framework Manager Identify reporting traps securityenvironment Use tools to analyze the model Model Maintenance and ExtensibilityCreate a baseline project Model for Predictable Results: Virtual Remap metadata to another sourceEnhance the model with additional metadata Star Schemas Import and link a second data sourcePrepare Reusable Metadata Model in layers Run scripts to automate or update a modelEnsure efficient filters by configuring prompt Create aliases to avoid ambiguous joins View lineageproperties Merge query subjects to create as view Create a model reportModel for Predictable Results: Identify behavior Optimize and Tune Framework ManagerReporting Issues Model for Predictable Results: ModelsDescribe how IBM Cognos BI uses Consolidate Metadata Work in a Multi-Modeler Environmentcardinality Create virtual dimensions to resolve Segment and link a projectIdentify reporting traps fact-to-fact joins Branch a project and merge resultsUse tools to analyze the model Create a consolidated modeling layer for Manage OLAP Data SourcesModel for Predictable Results: Virtual Star presentation purposes Publish an OLAP modelSchemas Consolidate snowflake dimensions with Publish a model with multiple OLAP dataModel in layers model query subjects sourcesCreate aliases to avoid ambiguous joins Simplify facts by hiding unnecessary Publish a model with an OLAP data sourceMerge query subjects to create as view codes and a relational data sourcebehavior Calculations and Filters Manage Framework Manager PackagesModel for Predictable Results: Consolidate Use static filters to reduce the data Control model versioningMetadata returned Nest packagesCreate virtual dimensions to resolve Use macros and parameters infact-to-fact joins calculations and filters to dynamicallyCreate a consolidated modeling layer for control the data returned linepresentation purposes Implement a Time Dimension Describe IBM Cognos componentsConsolidate snowflake dimensions with Resolve confusion caused by multiple Describe IBM Cognos architecture at amodel query subjects relationships between a time dimension high levelSimplify facts by hiding unnecessary codes and another table Define IBM Cognos groups and rolesCalculations and Filters Specify Determinants Explain how to extend IBM CognosUse static filters to reduce the data returned Create the Presentation View Identify Common Data StructuresUse macros and parameters in calculations Identify conformed vs. non-conformed Examine relationships and cardinalityand filters to dynamically control the data dimensions Identify different data trapsreturned Create star schema groupings to provide Examine OLAP data sourcesImplement a Time Dimension authors with logical groupings of query Gather RequirementsResolve confusion caused by multiple subjects Define reporting requirementsrelationships between a time dimension and Work with Different Query Subject Types Explore data sources to identify data


another table Identify the effects on generated SQL access strategiesSpecify Determinants when modifying query subjects, SQL Create a Baseline ProjectCreate the Presentation View settings and relationships Define a project and its structureIdentify conformed vs. non-conformed Set Security in Framework Manager Describe the Framework Managerdimensions Restrict access to packages environmentCreate star schema groupings to provide Create and apply security filters Create a baseline projectauthors with logical groupings of query Restrict access to objects in the model Enhance the model with additionalsubjects Create Analysis Objects metadataWork with Different Query Subject Types Sort members for presentation and Prepare Reusable MetadataIdentify the effects on generated SQL when predictability Ensure efficient filters by configuringmodifying query subjects, SQL settings and Manage MUNs in Framework Manager prompt propertiesrelationships Define members and member unique Model for Predictable Results: IdentifySet Security in Framework Manager names Reporting IssuesRestrict access to packages Identify changes that impact a MUN Describe how IBM Cognos BI usesCreate and apply security filters Model for Drill Through in Framework cardinalityRestrict access to objects in the model Manager Identify reporting trapsCreate Analysis Objects Define a report drill through Use tools to analyze the modelSort members for presentation and Define a package-based drill through Model for Predictable Results: Virtual Starpredictability Identify drill-through values SchemasManage MUNs in Framework Manager Advanced Generated SQL Concepts and Model in layersDefine members and member unique names Complex Queries Create aliases to avoid ambiguous joinsIdentify changes that impact a MUN Stitch query SQL Merge query subjects to create as viewModel for Drill Through in Framework Conformed and non-conformed behaviorManager dimensions in generated SQL Model for Predictable Results: ConsolidateDefine a report drill through Multi-fact/multi-grain stitch query SQL MetadataDefine a package-based drill through Variances in Report Studio generated Create virtual dimensions to resolveIdentify drill-through values SQL fact-to-fact joinsAdvanced Generated SQL Concepts and Dimensionally modeled relational SQL Create a consolidated modeling layer forComplex Queries generation presentation purposesStitch query SQL Cross join SQL Consolidate snowflake dimensions withConformed and non-conformed dimensions Various results sets for multi-fact queries model query subjectsin generated SQL Use Advanced Parameterization Simplify facts by hiding unnecessary codesMulti-fact/multi-grain stitch query SQL Techniques in Framework Manger Calculations and FiltersVariances in Report Studio generated SQL Leverage session, model, and custom Use static filters to reduce the dataDimensionally modeled relational SQL parameters returnedgeneration Create prompt macros Use macros and parameters inCross join SQL Leverage macro functions associated calculations and filters to dynamicallyVarious results sets for multi-fact queries with security control the data returnedUse Advanced Parameterization Techniques Model Maintenance and Extensibility Implement a Time Dimensionin Framework Manger Remap metadata to another source Resolve confusion caused by multipleLeverage session, model, and custom Import and link a second data source relationships between a time dimensionparameters Run scripts to automate or update a and another tableCreate prompt macros model Specify DeterminantsLeverage macro functions associated with View lineage Create the Presentation Viewsecurity Create a model report Identify conformed vs. non-conformedModel Maintenance and Extensibility Optimize and Tune Framework Manager dimensionsRemap metadata to another source Models Create star schema groupings to provideImport and link a second data source Work in a Multi-Modeler Environment authors with logical groupings of queryRun scripts to automate or update a model Segment and link a project subjectsView lineage Branch a project and merge results Work with Different Query Subject TypesCreate a model report Manage OLAP Data Sources Identify the effects on generated SQLOptimize and Tune Framework Manager Publish an OLAP model when modifying query subjects, SQLModels Publish a model with multiple OLAP data settings and relationshipsWork in a Multi-Modeler Environment sources Set Security in Framework ManagerSegment and link a project Publish a model with an OLAP data Restrict access to packagesBranch a project and merge results source and a relational data source Create and apply security filtersManage OLAP Data Sources Manage Framework Manager Packages Restrict access to objects in the modelPublish an OLAP model Control model versioning Create Analysis ObjectsPublish a model with multiple OLAP data Nest packages Sort members for presentation andsources predictabilityPublish a model with an OLAP data source Manage MUNs in Framework Managerand a relational data source line Define members and member uniqueManage Framework Manager Packages Discuss IBM Cognos and Performance namesControl model versioning Management Identify changes that impact a MUNNest packages Examine the characteristics of Model for Drill Through in Framework

operational databases and databases Manager


designed for reporting Define a report drill throughline Examine key modeling recommendations Define a package-based drill through

Describe IBM Cognos components Examine the IBM Cognos BI and Identify drill-through valuesDescribe IBM Cognos architecture at a high Framework Manager workflow processes Advanced Generated SQL Concepts andlevel Verify relationships and query item Complex QueriesDefine IBM Cognos groups and roles properties Stitch query SQLExplain how to extend IBM Cognos Describe multi-fact queries and when full Conformed and non-conformedIdentify Common Data Structures outer joins are appropriate dimensions in generated SQLExamine relationships and cardinality Identify the advantages of modeling Multi-fact/multi-grain stitch query SQLIdentify different data traps metadata as a star schema Variances in Report Studio generated SQLExamine OLAP data sources Create virtual facts to simplify writing Dimensionally modeled relational SQLGather Requirements queries generationDefine reporting requirements Use calculations to create Cross join SQLExplore data sources to identify data access commonly-needed query items for Various results sets for multi-fact queriesstrategies authors Use Advanced ParameterizationCreate a Baseline Project Make time-based queries simple to Techniques in Framework MangerDefine a project and its structure author by implementing a time dimension Leverage session, model, and customDescribe the Framework Manager Use determinants to specify multiple parametersenvironment levels of granularity and prevent Create prompt macrosCreate a baseline project double-counting Leverage macro functions associated withEnhance the model with additional metadata Identify the dimensions associated with a securityPrepare Reusable Metadata fact table Model Maintenance and ExtensibilityEnsure efficient filters by configuring prompt Identify key differences and Remap metadata to another sourceproperties recommendations for using data source, Import and link a second data sourceModel for Predictable Results: Identify model, and stored procedure query Run scripts to automate or update a modelReporting Issues subjects View lineageDescribe how IBM Cognos BI uses Examine the IBM Cognos BI security Create a model reportcardinality environment Optimize and Tune Framework ManagerIdentify reporting traps Apply dimensional information to ModelsUse tools to analyze the model relational Metadata to enable OLAP-style Work in a Multi-Modeler EnvironmentModel for Predictable Results: Virtual Star queries Segment and link a projectSchemas Describe model types and data entities Branch a project and merge resultsModel in layers Identify conformed values between data Manage OLAP Data SourcesCreate aliases to avoid ambiguous joins sources Publish an OLAP modelMerge query subjects to create as view Governors that affect SQL generation Publish a model with multiple OLAP databehavior Identify session and model parameters sourcesModel for Predictable Results: Consolidate Perform basic maintenance and Publish a model with an OLAP data sourceMetadata management on a model and a relational data sourceCreate virtual dimensions to resolve Identify and implement techniques to Manage Framework Manager Packagesfact-to-fact joins optimize and tune your Framework Control model versioningCreate a consolidated modeling layer for Manager models Nest packagespresentation purposes Implement repository controlConsolidate snowflake dimensions with Connect to an OLAP data source (cube)model query subjects in a Framework Manager project lineSimplify facts by hiding unnecessary codes Specify package languages and function Describe IBM Cognos componentsCalculations and Filters sets Describe IBM Cognos architecture at aUse static filters to reduce the data returned high levelUse macros and parameters in calculations Define IBM Cognos groups and rolesand filters to dynamically control the data line Explain how to extend IBM Cognosreturned Describe IBM Cognos components Identify Common Data StructuresImplement a Time Dimension Describe IBM Cognos architecture at a Examine relationships and cardinalityResolve confusion caused by multiple high level Identify different data trapsrelationships between a time dimension and Define IBM Cognos groups and roles Examine OLAP data sourcesanother table Explain how to extend IBM Cognos Gather RequirementsSpecify Determinants Identify Common Data Structures Define reporting requirementsCreate the Presentation View Examine relationships and cardinality Explore data sources to identify dataIdentify conformed vs. non-conformed Identify different data traps access strategiesdimensions Examine OLAP data sources Create a Baseline ProjectCreate star schema groupings to provide Gather Requirements Define a project and its structureauthors with logical groupings of query Define reporting requirements Describe the Framework Managersubjects Explore data sources to identify data environmentWork with Different Query Subject Types access strategies Create a baseline projectIdentify the effects on generated SQL when Create a Baseline Project Enhance the model with additionalmodifying query subjects, SQL settings and Define a project and its structure metadatarelationships Describe the Framework Manager Prepare Reusable MetadataSet Security in Framework Manager environment Ensure efficient filters by configuring


Restrict access to packages Create a baseline project prompt propertiesCreate and apply security filters Enhance the model with additional Model for Predictable Results: IdentifyRestrict access to objects in the model metadata Reporting IssuesCreate Analysis Objects Prepare Reusable Metadata Describe how IBM Cognos BI usesSort members for presentation and Ensure efficient filters by configuring cardinalitypredictability prompt properties Identify reporting trapsManage MUNs in Framework Manager Model for Predictable Results: Identify Use tools to analyze the modelDefine members and member unique names Reporting Issues Model for Predictable Results: Virtual StarIdentify changes that impact a MUN Describe how IBM Cognos BI uses SchemasModel for Drill Through in Framework cardinality Model in layersManager Identify reporting traps Create aliases to avoid ambiguous joinsDefine a report drill through Use tools to analyze the model Merge query subjects to create as viewDefine a package-based drill through Model for Predictable Results: Virtual behaviorIdentify drill-through values Star Schemas Model for Predictable Results: ConsolidateAdvanced Generated SQL Concepts and Model in layers MetadataComplex Queries Create aliases to avoid ambiguous joins Create virtual dimensions to resolveStitch query SQL Merge query subjects to create as view fact-to-fact joinsConformed and non-conformed dimensions behavior Create a consolidated modeling layer forin generated SQL Model for Predictable Results: presentation purposesMulti-fact/multi-grain stitch query SQL Consolidate Metadata Consolidate snowflake dimensions withVariances in Report Studio generated SQL Create virtual dimensions to resolve model query subjectsDimensionally modeled relational SQL fact-to-fact joins Simplify facts by hiding unnecessary codesgeneration Create a consolidated modeling layer for Calculations and FiltersCross join SQL presentation purposes Use static filters to reduce the dataVarious results sets for multi-fact queries Consolidate snowflake dimensions with returnedUse Advanced Parameterization Techniques model query subjects Use macros and parameters inin Framework Manger Simplify facts by hiding unnecessary calculations and filters to dynamicallyLeverage session, model, and custom codes control the data returnedparameters Calculations and Filters Implement a Time DimensionCreate prompt macros Use static filters to reduce the data Resolve confusion caused by multipleLeverage macro functions associated with returned relationships between a time dimensionsecurity Use macros and parameters in and another tableModel Maintenance and Extensibility calculations and filters to dynamically Specify DeterminantsRemap metadata to another source control the data returned Create the Presentation ViewImport and link a second data source Implement a Time Dimension Identify conformed vs. non-conformedRun scripts to automate or update a model Resolve confusion caused by multiple dimensionsView lineage relationships between a time dimension Create star schema groupings to provideCreate a model report and another table authors with logical groupings of queryOptimize and Tune Framework Manager Specify Determinants subjectsModels Create the Presentation View Work with Different Query Subject TypesWork in a Multi-Modeler Environment Identify conformed vs. non-conformed Identify the effects on generated SQLSegment and link a project dimensions when modifying query subjects, SQLBranch a project and merge results Create star schema groupings to provide settings and relationshipsManage OLAP Data Sources authors with logical groupings of query Set Security in Framework ManagerPublish an OLAP model subjects Restrict access to packagesPublish a model with multiple OLAP data Work with Different Query Subject Types Create and apply security filterssources Identify the effects on generated SQL Restrict access to objects in the modelPublish a model with an OLAP data source when modifying query subjects, SQL Create Analysis Objectsand a relational data source settings and relationships Sort members for presentation andManage Framework Manager Packages Set Security in Framework Manager predictabilityControl model versioning Restrict access to packages Manage MUNs in Framework ManagerNest packages Create and apply security filters Define members and member unique

Restrict access to objects in the model namesCreate Analysis Objects Identify changes that impact a MUN

line Sort members for presentation and Model for Drill Through in FrameworkDiscuss IBM Cognos and Performance predictability ManagerManagement Manage MUNs in Framework Manager Define a report drill throughExamine the characteristics of operational Define members and member unique Define a package-based drill throughdatabases and databases designed for names Identify drill-through valuesreporting Identify changes that impact a MUN Advanced Generated SQL Concepts andExamine key modeling recommendations Model for Drill Through in Framework Complex QueriesExamine the IBM Cognos BI and Framework Manager Stitch query SQLManager workflow processes Define a report drill through Conformed and non-conformedVerify relationships and query item Define a package-based drill through dimensions in generated SQLproperties Identify drill-through values Multi-fact/multi-grain stitch query SQLDescribe multi-fact queries and when full Advanced Generated SQL Concepts and Variances in Report Studio generated SQL


outer joins are appropriate Complex Queries Dimensionally modeled relational SQLIdentify the advantages of modeling Stitch query SQL generationmetadata as a star schema Conformed and non-conformed Cross join SQLCreate virtual facts to simplify writing queries dimensions in generated SQL Various results sets for multi-fact queriesUse calculations to create Multi-fact/multi-grain stitch query SQL Use Advanced Parameterizationcommonly-needed query items for authors Variances in Report Studio generated Techniques in Framework MangerMake time-based queries simple to author SQL Leverage session, model, and customby implementing a time dimension Dimensionally modeled relational SQL parametersUse determinants to specify multiple levels generation Create prompt macrosof granularity and prevent double-counting Cross join SQL Leverage macro functions associated withIdentify the dimensions associated with a Various results sets for multi-fact queries securityfact table Use Advanced Parameterization Model Maintenance and ExtensibilityIdentify key differences and Techniques in Framework Manger Remap metadata to another sourcerecommendations for using data source, Leverage session, model, and custom Import and link a second data sourcemodel, and stored procedure query subjects parameters Run scripts to automate or update a modelExamine the IBM Cognos BI security Create prompt macros View lineageenvironment Leverage macro functions associated Create a model reportApply dimensional information to relational with security Optimize and Tune Framework ManagerMetadata to enable OLAP-style queries Model Maintenance and Extensibility ModelsDescribe model types and data entities Remap metadata to another source Work in a Multi-Modeler EnvironmentIdentify conformed values between data Import and link a second data source Segment and link a projectsources Run scripts to automate or update a Branch a project and merge resultsGovernors that affect SQL generation model Manage OLAP Data SourcesIdentify session and model parameters View lineage Publish an OLAP modelPerform basic maintenance and Create a model report Publish a model with multiple OLAP datamanagement on a model Optimize and Tune Framework Manager sourcesIdentify and implement techniques to Models Publish a model with an OLAP data sourceoptimize and tune your Framework Manager Work in a Multi-Modeler Environment and a relational data sourcemodels Segment and link a project Manage Framework Manager PackagesImplement repository control Branch a project and merge results Control model versioningConnect to an OLAP data source (cube) in a Manage OLAP Data Sources Nest packagesFramework Manager project Publish an OLAP modelSpecify package languages and function Publish a model with multiple OLAP datasets sources line

Publish a model with an OLAP data Discuss IBM Cognos and Performancesource and a relational data source Management

line Manage Framework Manager Packages Examine the characteristics of operationalDescribe IBM Cognos components Control model versioning databases and databases designed forDescribe IBM Cognos architecture at a high Nest packages reportinglevel Examine key modeling recommendationsDefine IBM Cognos groups and roles Examine the IBM Cognos BI andExplain how to extend IBM Cognos line Framework Manager workflow processesIdentify Common Data Structures Describe IBM Cognos components Verify relationships and query itemExamine relationships and cardinality Describe IBM Cognos architecture at a propertiesIdentify different data traps high level Describe multi-fact queries and when fullExamine OLAP data sources Define IBM Cognos groups and roles outer joins are appropriateGather Requirements Explain how to extend IBM Cognos Identify the advantages of modelingDefine reporting requirements Identify Common Data Structures metadata as a star schemaExplore data sources to identify data access Examine relationships and cardinality Create virtual facts to simplify writingstrategies Identify different data traps queriesCreate a Baseline Project Examine OLAP data sources Use calculations to createDefine a project and its structure Gather Requirements commonly-needed query items for authorsDescribe the Framework Manager Define reporting requirements Make time-based queries simple to authorenvironment Explore data sources to identify data by implementing a time dimensionCreate a baseline project access strategies Use determinants to specify multiple levelsEnhance the model with additional metadata Create a Baseline Project of granularity and prevent double-countingPrepare Reusable Metadata Define a project and its structure Identify the dimensions associated with aEnsure efficient filters by configuring prompt Describe the Framework Manager fact tableproperties environment Identify key differences andModel for Predictable Results: Identify Create a baseline project recommendations for using data source,Reporting Issues Enhance the model with additional model, and stored procedure queryDescribe how IBM Cognos BI uses metadata subjectscardinality Prepare Reusable Metadata Examine the IBM Cognos BI securityIdentify reporting traps Ensure efficient filters by configuring environmentUse tools to analyze the model prompt properties Apply dimensional information to relationalModel for Predictable Results: Virtual Star Model for Predictable Results: Identify Metadata to enable OLAP-style queries


Schemas Reporting Issues Describe model types and data entitiesModel in layers Describe how IBM Cognos BI uses Identify conformed values between dataCreate aliases to avoid ambiguous joins cardinality sourcesMerge query subjects to create as view Identify reporting traps Governors that affect SQL generationbehavior Use tools to analyze the model Identify session and model parametersModel for Predictable Results: Consolidate Model for Predictable Results: Virtual Perform basic maintenance andMetadata Star Schemas management on a modelCreate virtual dimensions to resolve Model in layers Identify and implement techniques tofact-to-fact joins Create aliases to avoid ambiguous joins optimize and tune your FrameworkCreate a consolidated modeling layer for Merge query subjects to create as view Manager modelspresentation purposes behavior Implement repository controlConsolidate snowflake dimensions with Model for Predictable Results: Connect to an OLAP data source (cube) inmodel query subjects Consolidate Metadata a Framework Manager projectSimplify facts by hiding unnecessary codes Create virtual dimensions to resolve Specify package languages and functionCalculations and Filters fact-to-fact joins setsUse static filters to reduce the data returned Create a consolidated modeling layer forUse macros and parameters in calculations presentation purposesand filters to dynamically control the data Consolidate snowflake dimensions with linereturned model query subjects Describe IBM Cognos componentsImplement a Time Dimension Simplify facts by hiding unnecessary Describe IBM Cognos architecture at aResolve confusion caused by multiple codes high levelrelationships between a time dimension and Calculations and Filters Define IBM Cognos groups and rolesanother table Use static filters to reduce the data Explain how to extend IBM CognosSpecify Determinants returned Identify Common Data StructuresCreate the Presentation View Use macros and parameters in Examine relationships and cardinalityIdentify conformed vs. non-conformed calculations and filters to dynamically Identify different data trapsdimensions control the data returned Examine OLAP data sourcesCreate star schema groupings to provide Implement a Time Dimension Gather Requirementsauthors with logical groupings of query Resolve confusion caused by multiple Define reporting requirementssubjects relationships between a time dimension Explore data sources to identify dataWork with Different Query Subject Types and another table access strategiesIdentify the effects on generated SQL when Specify Determinants Create a Baseline Projectmodifying query subjects, SQL settings and Create the Presentation View Define a project and its structurerelationships Identify conformed vs. non-conformed Describe the Framework ManagerSet Security in Framework Manager dimensions environmentRestrict access to packages Create star schema groupings to provide Create a baseline projectCreate and apply security filters authors with logical groupings of query Enhance the model with additionalRestrict access to objects in the model subjects metadataCreate Analysis Objects Work with Different Query Subject Types Prepare Reusable MetadataSort members for presentation and Identify the effects on generated SQL Ensure efficient filters by configuringpredictability when modifying query subjects, SQL prompt propertiesManage MUNs in Framework Manager settings and relationships Model for Predictable Results: IdentifyDefine members and member unique names Set Security in Framework Manager Reporting IssuesIdentify changes that impact a MUN Restrict access to packages Describe how IBM Cognos BI usesModel for Drill Through in Framework Create and apply security filters cardinalityManager Restrict access to objects in the model Identify reporting trapsDefine a report drill through Create Analysis Objects Use tools to analyze the modelDefine a package-based drill through Sort members for presentation and Model for Predictable Results: Virtual StarIdentify drill-through values predictability SchemasAdvanced Generated SQL Concepts and Manage MUNs in Framework Manager Model in layersComplex Queries Define members and member unique Create aliases to avoid ambiguous joinsStitch query SQL names Merge query subjects to create as viewConformed and non-conformed dimensions Identify changes that impact a MUN behaviorin generated SQL Model for Drill Through in Framework Model for Predictable Results: ConsolidateMulti-fact/multi-grain stitch query SQL Manager MetadataVariances in Report Studio generated SQL Define a report drill through Create virtual dimensions to resolveDimensionally modeled relational SQL Define a package-based drill through fact-to-fact joinsgeneration Identify drill-through values Create a consolidated modeling layer forCross join SQL Advanced Generated SQL Concepts and presentation purposesVarious results sets for multi-fact queries Complex Queries Consolidate snowflake dimensions withUse Advanced Parameterization Techniques Stitch query SQL model query subjectsin Framework Manger Conformed and non-conformed Simplify facts by hiding unnecessary codesLeverage session, model, and custom dimensions in generated SQL Calculations and Filtersparameters Multi-fact/multi-grain stitch query SQL Use static filters to reduce the dataCreate prompt macros Variances in Report Studio generated returnedLeverage macro functions associated with SQL Use macros and parameters in


security Dimensionally modeled relational SQL calculations and filters to dynamicallyModel Maintenance and Extensibility generation control the data returnedRemap metadata to another source Cross join SQL Implement a Time DimensionImport and link a second data source Various results sets for multi-fact queries Resolve confusion caused by multipleRun scripts to automate or update a model Use Advanced Parameterization relationships between a time dimensionView lineage Techniques in Framework Manger and another tableCreate a model report Leverage session, model, and custom Specify DeterminantsOptimize and Tune Framework Manager parameters Create the Presentation ViewModels Create prompt macros Identify conformed vs. non-conformedWork in a Multi-Modeler Environment Leverage macro functions associated dimensionsSegment and link a project with security Create star schema groupings to provideBranch a project and merge results Model Maintenance and Extensibility authors with logical groupings of queryManage OLAP Data Sources Remap metadata to another source subjectsPublish an OLAP model Import and link a second data source Work with Different Query Subject TypesPublish a model with multiple OLAP data Run scripts to automate or update a Identify the effects on generated SQLsources model when modifying query subjects, SQLPublish a model with an OLAP data source View lineage settings and relationshipsand a relational data source Create a model report Set Security in Framework ManagerManage Framework Manager Packages Optimize and Tune Framework Manager Restrict access to packagesControl model versioning Models Create and apply security filtersNest packages Work in a Multi-Modeler Environment Restrict access to objects in the model

Segment and link a project Create Analysis ObjectsBranch a project and merge results Sort members for presentation andManage OLAP Data Sources predictabilityPublish an OLAP model Manage MUNs in Framework ManagerPublish a model with multiple OLAP data Define members and member uniquesources namesPublish a model with an OLAP data Identify changes that impact a MUNsource and a relational data source Model for Drill Through in FrameworkManage Framework Manager Packages ManagerControl model versioning Define a report drill throughNest packages Define a package-based drill through

Identify drill-through valuesAdvanced Generated SQL Concepts and

line Complex QueriesDescribe IBM Cognos components Stitch query SQLDescribe IBM Cognos architecture at a Conformed and non-conformedhigh level dimensions in generated SQLDefine IBM Cognos groups and roles Multi-fact/multi-grain stitch query SQLExplain how to extend IBM Cognos Variances in Report Studio generated SQLIdentify Common Data Structures Dimensionally modeled relational SQLExamine relationships and cardinality generationIdentify different data traps Cross join SQLExamine OLAP data sources Various results sets for multi-fact queriesGather Requirements Use Advanced ParameterizationDefine reporting requirements Techniques in Framework MangerExplore data sources to identify data Leverage session, model, and customaccess strategies parametersCreate a Baseline Project Create prompt macrosDefine a project and its structure Leverage macro functions associated withDescribe the Framework Manager securityenvironment Model Maintenance and ExtensibilityCreate a baseline project Remap metadata to another sourceEnhance the model with additional Import and link a second data sourcemetadata Run scripts to automate or update a modelPrepare Reusable Metadata View lineageEnsure efficient filters by configuring Create a model reportprompt properties Optimize and Tune Framework ManagerModel for Predictable Results: Identify ModelsReporting Issues Work in a Multi-Modeler EnvironmentDescribe how IBM Cognos BI uses Segment and link a projectcardinality Branch a project and merge resultsIdentify reporting traps Manage OLAP Data SourcesUse tools to analyze the model Publish an OLAP modelModel for Predictable Results: Virtual Publish a model with multiple OLAP dataStar Schemas sources


Model in layers Publish a model with an OLAP data sourceCreate aliases to avoid ambiguous joins and a relational data sourceMerge query subjects to create as view Manage Framework Manager Packagesbehavior Control model versioningModel for Predictable Results: Nest packagesConsolidate MetadataCreate virtual dimensions to resolvefact-to-fact joins lineCreate a consolidated modeling layer for Describe IBM Cognos componentspresentation purposes Describe IBM Cognos architecture at aConsolidate snowflake dimensions with high levelmodel query subjects Define IBM Cognos groups and rolesSimplify facts by hiding unnecessary Explain how to extend IBM Cognoscodes Identify Common Data StructuresCalculations and Filters Examine relationships and cardinalityUse static filters to reduce the data Identify different data trapsreturned Examine OLAP data sourcesUse macros and parameters in Gather Requirementscalculations and filters to dynamically Define reporting requirementscontrol the data returned Explore data sources to identify dataImplement a Time Dimension access strategiesResolve confusion caused by multiple Create a Baseline Projectrelationships between a time dimension Define a project and its structureand another table Describe the Framework ManagerSpecify Determinants environmentCreate the Presentation View Create a baseline projectIdentify conformed vs. non-conformed Enhance the model with additionaldimensions metadataCreate star schema groupings to provide Prepare Reusable Metadataauthors with logical groupings of query Ensure efficient filters by configuringsubjects prompt propertiesWork with Different Query Subject Types Model for Predictable Results: IdentifyIdentify the effects on generated SQL Reporting Issueswhen modifying query subjects, SQL Describe how IBM Cognos BI usessettings and relationships cardinalitySet Security in Framework Manager Identify reporting trapsRestrict access to packages Use tools to analyze the modelCreate and apply security filters Model for Predictable Results: Virtual StarRestrict access to objects in the model SchemasCreate Analysis Objects Model in layersSort members for presentation and Create aliases to avoid ambiguous joinspredictability Merge query subjects to create as viewManage MUNs in Framework Manager behaviorDefine members and member unique Model for Predictable Results: Consolidatenames MetadataIdentify changes that impact a MUN Create virtual dimensions to resolveModel for Drill Through in Framework fact-to-fact joinsManager Create a consolidated modeling layer forDefine a report drill through presentation purposesDefine a package-based drill through Consolidate snowflake dimensions withIdentify drill-through values model query subjectsAdvanced Generated SQL Concepts and Simplify facts by hiding unnecessary codesComplex Queries Calculations and FiltersStitch query SQL Use static filters to reduce the dataConformed and non-conformed returneddimensions in generated SQL Use macros and parameters inMulti-fact/multi-grain stitch query SQL calculations and filters to dynamicallyVariances in Report Studio generated control the data returnedSQL Implement a Time DimensionDimensionally modeled relational SQL Resolve confusion caused by multiplegeneration relationships between a time dimensionCross join SQL and another tableVarious results sets for multi-fact queries Specify DeterminantsUse Advanced Parameterization Create the Presentation ViewTechniques in Framework Manger Identify conformed vs. non-conformedLeverage session, model, and custom dimensions


parameters Create star schema groupings to provideCreate prompt macros authors with logical groupings of queryLeverage macro functions associated subjectswith security Work with Different Query Subject TypesModel Maintenance and Extensibility Identify the effects on generated SQLRemap metadata to another source when modifying query subjects, SQLImport and link a second data source settings and relationshipsRun scripts to automate or update a Set Security in Framework Managermodel Restrict access to packagesView lineage Create and apply security filtersCreate a model report Restrict access to objects in the modelOptimize and Tune Framework Manager Create Analysis ObjectsModels Sort members for presentation andWork in a Multi-Modeler Environment predictabilitySegment and link a project Manage MUNs in Framework ManagerBranch a project and merge results Define members and member uniqueManage OLAP Data Sources namesPublish an OLAP model Identify changes that impact a MUNPublish a model with multiple OLAP data Model for Drill Through in Frameworksources ManagerPublish a model with an OLAP data Define a report drill throughsource and a relational data source Define a package-based drill throughManage Framework Manager Packages Identify drill-through valuesControl model versioning Advanced Generated SQL Concepts andNest packages Complex Queries

Stitch query SQLConformed and non-conformeddimensions in generated SQLMulti-fact/multi-grain stitch query SQLVariances in Report Studio generated SQLDimensionally modeled relational SQLgenerationCross join SQLVarious results sets for multi-fact queriesUse Advanced ParameterizationTechniques in Framework MangerLeverage session, model, and customparametersCreate prompt macrosLeverage macro functions associated withsecurityModel Maintenance and ExtensibilityRemap metadata to another sourceImport and link a second data sourceRun scripts to automate or update a modelView lineageCreate a model reportOptimize and Tune Framework ManagerModelsWork in a Multi-Modeler EnvironmentSegment and link a projectBranch a project and merge resultsManage OLAP Data SourcesPublish an OLAP modelPublish a model with multiple OLAP datasourcesPublish a model with an OLAP data sourceand a relational data sourceManage Framework Manager PackagesControl model versioningNest packages


Más información:

Para más información o para reservar tu plaza llámanos al (34) 91 425 06 60

[email protected]

www.globalknowledge.es

Global Knowledge Network Spain, C/ Retama 7, 6ª planta, 28045 Madrid

http://www.globalknowledge.es

Date post:	25-May-2021
Category:	Documents
Upload:	others
View:	8 times
Download:	0 times

IBM Cognos Framework Manager: Design Metadata Models (V10.1) · IBM Cognos Framework Manager:...

Documents