Bods Question

8/11/2019 Bods Question

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1. What is the use of Business Objects Data Services?

Answer:

Business Objects Data Services provides a graphical interface that allows you to easily create jobs that extract data from

heterogeneous sources, transform that data to meet the business requirements of your organization, and load the data

into a single location.

2. Define Data Services components.

Answer:

Data Services includes the following standard components:

Designer

Repository Job Server

Engines Access Server

Adapters

Real-time Services Address Server Cleansing Packages, Dictionaries, and Directories

Management Console

3. What are the steps included in Data integration process?

To know the answer of this question and similar high frequency Data Services questions, please continue to,

3. What are the steps included in Data integration process?

Answer:

Stage data in an operational data store, data warehouse, or data mart. Update staged data in batch or real-time modes.

Create a single environment for developing, testing, and deploying the entire data integration platform. Manage a single metadata repository to capture the relationships between different extraction and access

methods and provide integrated lineage and impact analysis.

4. Define the terms Job, Workflow, and Dataflow

Answer:

A job is the smallest unit of work that you can schedule independently for execution. A work flow defines the decision-making process for executing data flows.

Data flows extract, transform, and load data. Everything having to do with data, including reading sources,

transforming data, and loading targets, occurs inside a data flow.


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5. Arrange these objects in order by their hierarchy: Dataflow, Job, Project, and Workflow.

Answer

Project, Job, Workflow, Dataflow.

6. What are reusable objects in Data Services?

Answer:

Job, Workflow, Dataflow.

7. What is a transform?

Answer:

A transform enables you to control how datasets change in a dataflow.

8. What is a Script?

Answer:

A script is a single-use object that is used to call functions and assign values in a workflow.

9. What is a real time Job?

Answer:

Real-time jobs "extract" data from the body of the real time message received and from any secondary sources used inthe job.

10. What is an Embedded Dataflow?

Answer:

An Embedded Dataflow is a dataflow that is called from inside another dataflow.

11. What is the difference between a data store and a database?

Answer:

A datastore is a connection to a database.


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12. How many types of data stores are present in Data services?

Answer:

Three.

Database Datastores: provide a simple way to import metadata directly from an RDBMS.

Application Datastores: let users easily import metadata from most Enterprise Resource Planning (ERP) systems.

Adapter Datastores: can provide access to an applications data and metadata or just metadata. 13. What is the use of Compace repository?

Answer:

Remove redundant and obsolete objects from the repository tables.

14. What are Memory Datastores?

Answer:

Data Services also allows you to create a database data store using Memory as the Database type. Memory Datastoresare designed to enhance processing performance of data flows executing in real-time jobs.

15. What are file formats?

Answer:

A file format is a set of properties describing the structure of a flat file (ASCII). File formats describe the metadatastructure. File format objects can describe files in:

Delimited format Characters such as commas or tabs separate each field.

Fixed width format The column width is specified by the user. SAP ERP and R/3 format.

16. Which is NOT a datastore type?

Answer:

File Format

17. What is repository? List the types of repositories.

Answer:

The DataServices repository is a set of tables that holds user-created and predefined system objects, source and target

metadata, and transformation rules. There are 3 types of repositories.


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A local repository A central repository A profiler repository

18. What is the difference between a Repository and a Datastore?

Answer:

A Repository is a set of tables that hold system objects, source and target metadata, and transformation rules. A

Datastore is an actual connection to a database that holds data.

19. What is the difference between a Parameter and a Variable?

Answer:

A Parameter is an expression that passes a piece of information to a work flow, data flow or custom function when it is

called in a job. A Variable is a symbolic placeholder for values.

20. When would you use a global variable instead of a local variable?

Answer:

When the variable will need to be used multiple times within a job. When you want to reduce the development time required for passing values between job components.

When you need to create a dependency between job level global variable name and job components.21. What is Substitution Parameter?

Answer:

The Value that is constant in one environment, but may change when a job is migrated to another environment.

22. List some reasons why a job might fail to execute?

Answer:

Incorrect syntax, Job Server not running, port numbers for Designer and Job Server not matching.

23. List factors you consider when determining whether to run work flows or data flows serially or in parallel?

Answer:

Consider the following:

Whether or not the flows are independent of each other

Whether or not the server can handle the processing requirements of flows running at the same time ( in parallel)24. What does a lookup function do? How do the different variations of the lookup function differ?

Answer:


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All lookup functions return one row for each row in the source. They differ in how they choose which of severalmatching rows to return.

' 25. List the three types of input formats accepted by the Address Cleanse transform.

Answer:

Discrete, multiline, and hybrid.

26. Name the transform that you would use to combine incoming data sets to produce a single output data set with the

same schema as the input data sets.

Answer:

The Merge transform.

27. What are Adapters?

Answer:

Adapters are additional Java-based programs that can be installed on the job server to provide connectivity to othersystems such as Salesforce.com or the JavaMessagingQueue. There is also a SoftwareDevelopment Kit (SDK) to a llowcustomers to create adapters for custom applications.

28. List the data integrator transforms

Answer:

Data_Transfer Date_Generation Effective_Date

Hierarchy_Flattening History_Preserving Key_Generation

Map_CDC_Operation Pivot Reverse Pivot Table_Comparison

XML_Pipeline

29. List the Data Quality Transforms

Answer:

Global_Address_Cleanse

Data_Cleanse Match Associate

Country_id USA_Regulatory_Address_Cleanse


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30. What are Cleansing Packages?

Answer:

These are packages that enhance the ability of Data Cleanse to accurately process various forms of global data by

including language-specific reference data and parsing rules.

31. What is Data Cleanse?

Answer:

The Data Cleanse transform identifies and isolates specific parts of mixed data, and standardizes your data based on

information stored in the parsing dictionary, business rules defined in the rule file, and expressions defined in thepattern file.

32. What is the difference between Dictionary and Directory?

Answer:

Directories provide information on addresses from postal authorities. Dictionary files are used to identify, parse, and

standardize data such as names, titles, and firm data.

33. Give some examples of how data can be enhanced through the data cleanse transform, and describe the benefit ofthose enhancements.

Answer:

Enhancement Benefit

Determine gender distributions and target Gender Codes marketing campaigns Provide fields for improving matching Match Standards results

34. A project requires the parsing of names into given and family, validating address information, and findingduplicates across several systems. Name the transforms needed and the task they will perform.

Answer:

Data Cleanse: Parse names into given and family. Address Cleanse: Validate address information.

Match: Find duplicates.

35. Describe when to use the USA Regulatory and Global Address Cleanse transforms.

Answer:

Use the USA Regulatory transform if USPS certification and/or additional options such as DPV and Geocode are required.

Global Address Cleanse should be utilized when processing multi-country data.

36. Give two examples of how the Data Cleanse transform can enhance (append) data.


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Answer:

The Data Cleanse transform can generate name match standards and greetings. It can also assign gender codes andprenames such as Mr. and Mrs.

37. What are name match standards and how are they used?

Answer:

Name match standards illustrate the multiple ways a name can be represented.They are used in the match process togreatly increase match results.

38. What are the different strategies you can use to avoid duplicate rows of data when re-loading a job.

Answer:

Using the auto-correct load option in the target table.

Including the Table Comparison transform in the data flow. Designing the data flow to completely replace the target table during each execution.

Including a preload SQL statement to execute before the table loads.39. What is the use of Auto Correct Load?

Answer:

It does not allow duplicated data entering into the target table.It works like Type 1 Insert else Update the rows based on

Non-matching and matching data respectively.

40. What is the use of Array fetch size?

Answer:

Array fetch size indicates the number of rows retrieved in a single request to a source database. The default value is1000. Higher numbers reduce requests, lowering network traffic, and possibly improve performance. The maximum

value is 5000

41. What are the difference between Row-by-row select and Cached comparison table and sorted input in Table

Comparison Tranform?

Answer:

Row-by-row select look up the target table using SQL every time it receives an input row. This option is best ifthe target table is large.

Cached comparison table To load the comparison table into memory. This option is best when the table fits

into memory and you are comparing the entire target table Sorted input To read the comparison table in the order of the primary key column(s) using sequential read.

This option improves performance because Data Integrator reads the comparison table only once. Add a querybetween the source and the Table_Compari son transform. Then, from the querys input schema, drag the

primary key columns into the Order By box of the query.


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42. What is the use of using Number of loaders in Target Table?

Answer:

Number of loaders loading with one loader is known as Single loader Loading . Loading when the number of loaders is

greater than one is known as Parallel Loading . The default number of loaders is 1. The maximum number of loaders is5.

43. What is the use of Rows per commit?

Answer:

Specifies the transaction size in number of rows. If set to 1000, Data Integrator sends a commit to the underlyingdatabase every 1000 rows.

44. What is the difference between lookup (), lookup_ext () and lookup_seq ()?

Answer:

lookup() : Briefly, It returns single value based on single condition

lookup_ext(): It returns multiple values based on single/multiple condition(s) lookup_seq(): It returns multiple values based on sequence number

45. What is the use of History preserving transform?

Answer:

The History_Preserving transform allows you to produce a new row in your target rather than updating an existing row.

You can indicate in which columns the transform identifies changes to be preserved. If the value of certain columnschange, this transform creates a new row for each row flagged as UPDATE in the input data set.

46. What is the use of Map-Operation Transfrom?

Answer:

The Map_Operation transform allows you to change operation codes on data sets to produce the desired output.Operation codes: INSERT UPDATE, DELETE, NORMAL, or DISCARD.

47. What is Heirarchy Flatenning?

Answer:

Constructs a complete hierarchy from parent/child relationships, and then produces a description of the hierarchy invertically or horizontally flattened format.

Parent Column, Child Column

Parent Attributes, Child Attributes.48. What is the use of Case Transform?


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Answer:

Use the Case transform to simplify branch logic in data flows by consolidating case or decision-making logic into onetransform. The transform allows you to split a data set into smaller sets based on logical branches.

49. What must you define in order to audit a data flow?

Answer:

You must define audit points and audit rules when you want to audit a data flow.

50. List some factors for PERFORMANCE TUNING in data services?

Answer:

The following sections describe ways you can adjust Data Integrator performance

Source-based performance options Using array fetch size Caching data

Join ordering Minimizing extracted data Target-based performance options

Loading method and rows per commit Staging tables to speed up auto-correct loads

Job design performance options

Improving throughput Maximizing the number of pushed-down operations Minimizing data type conversion

Minimizing locale conversion Improving Informix repository performance

51. What is the purpose of database schema? Where can I find more information about this? It s not table, it s notdatabase, what is it?

A database schema is a way to logically group objects such as tables, views, stored procedures etc. Think of aschema as a container of objects.

You can assign a user login permissions to a single schema so that the user can only access the objects they areauthorized to access.

Schemas can be created and altered in a database, and users can be granted access to a schema. A schema can

be owned by any user, and schema ownership is transferable.

52. Difference between database and schema. (What s the difference between a Database and a Schema in SQL Server?

Both are the containers of tables and data.If a Schema is deleted, then are all the tables contained in that schema also

deleted automatically or they are deleted when the Database is deleted?)
http://stackoverflow.com/questions/5323740/difference-between-database-and-schemahttp://stackoverflow.com/questions/5323740/difference-between-database-and-schema


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Schema says what tables are in database, what columns they have and how they are related. Each database hasits own schema.

Schema is a way of categorising the objects in a database. It can be usefull if you have several applications share

a single database and while there is some common set of data that all application accesses. A database is the main container, it contains the data and log files, and all the schemas within it. You always

back up a database, it is a discrete unit on its own. Schemas are like folders within a database, and are mainly used to group logical objects together, which leads to

ease of setting permissions by schema.

Database is like container of data with schema, and schemas is layout of the tables there data types, relationsand stuff.

SAP DS (Data Services)

What are SAP DS (Data Services) good for? The aim SAP is pursuing with its SAP DS product isoptimize and improve your data quality with the aid of simple and efficient data integration options. As anETL (extract, transform, load) tool, SAP DS (former SAP BODS) lets you extract data from numeroussystem- and manufacturer- independent sources. Using the SAP DS native "data profiling" functionsallows you to analyze the existing quality of your data in advance, and in the process identify and assessproblems.

The quality and integrity of your data is crucial for the quality of information and the confidence you canhave in your decisions. SAP DS helps you integrate your company-wide fragmented data and improveyour data quality.

How does SAP DS optimize your data integration and improve your data quality?

As an ETL tool (extract, transform, load), SAP DS allows you to extract data from numerous sources,regardless of the respective systems and providers. The integrated data profiling functions help you

analyze the quality of your existing data in advance, allowing you to identify and analyze problems.

How does SAP DS operate?

You harmonize your data during the transformation phase, eliminate duplicates, standardize andvalidate, and enrich it with supplementary information. This ensures that only valid data according topredefined rules is transported into your target systems. With the help of process auditing, you can alsoestablish when a data transfer is to be considered successful or not beyond atomic validation rules.


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Integrated metadata management supports detailed tracing of precisely how the value in a target fieldwas generated by your transformation process (lineage analysis) and what the effects of changes wouldbe (impact analysis).

Distinguishing features of SAP DS (Data Services) include its outstanding performance and intuit iveoperation. All integration and data quality processes are developed and managed in a single interface,the Data Services Designer". C entralizing functions reduce development and maintenance effort. Auniform web interface that is separate from the development environment, the Data ServicesManagement Console, is used for operation and administration.

Data profiling, data integration and the improvement of data quality are key objectives whenimplementing an enterprise information management (EIM) initiative. Here SAP DS (former SAP BODS)serves as an initial and ongoing data quality gateway for your data. Whether you have problems w ithduplicate customer records in your ERP system, want to validate incoming material data depending onvalues, or want to load data from your CRM system and various Excel sheets into a data warehouseafter cleansing it, DS supports you with all types of data integration and data quality tasks right from theoutset. Especially in conjunction with data warehouse and master data management solutions, it makesan important contribution towards the effectiveness and efficiency of you EIM.

SAP BODS Training course contents DW Concepts

DefinitionMethodologiesDimensional ModelingDW LifecycleDW Challenges

ETL Overview ETL introductionStaging Area

Business RulesPerformanceSlowly Changing DimensionsSurrogate KeysFacts and Dimension TablesDifferent ETL Tools

Business Objects Overview HistoryComponents

Architecture

Data Services

Purpose of Data ServicesData Services architectureDefine Data Services objectsData Services Designer interface

Data Services Objects Object HierarchyJobsWorkflows


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Data Flows

Source and Target Metadata Data StoresFile formats for flat filesFile formats for Excel files

File formats for XML filesLab Exercises

Environment setup Creating repositorySetting Job ServerSetup for realtime operationSetting multiple datastoresStarting Job serversLab Exercises

Batch Jobs Work with objects

Create a data flowUse the Query transformUse target tablesExecute the jobLab Exercises

Troubleshooting Jobs Use descriptions and annotationsValidate and tracing jobsUse View Data and the Interactive DebuggerUse auditing in data flowsLab Exercises

Functions, Scripts and Variables Define built-in functionsFunctions in expressionsLookup functionDecode functionVariables and parametersData Services scripting languageScripting custom functionsLab Exercises

Important Transforms Map Operation transformValidation transformMerge transformCase transformSQL transformLab Exercises

Other Transforms Pivot transformHierarchy Flattening transformData Transfer transform


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XML Pipeline transformLab ExercisesError Handling Error HandlingRecoverable work flows

Change Data Capture Update data over timeDatabase native CDC mechanismsSource-based CDCTarget ComparisonLab Exercises

Data quality Overview Fundamentals of DQ and Data CleansingBuilt in DQ TransformationsData ValidationName & Address cleansingDe duplication

Cleansing other dataLab Exercises

Web-Services and Real-Time Integration Real Time JobsSOAP IntroductionWeb Services

SAP Integration Creating datastores for SAP databases

Accessing SAP dataRunning ABAP programsR/3 Data flows


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