EPM 309: Business Intelligence with the MPM Data WarehouseEPM 309

May 16, 2011

Presented byTaiwo Awosika

SGT, Inc.

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Agenda

May 16, 2011

Overview of Data WarehouseBenefits of Data WarehouseMPM Data Warehouse Structure (Project, WBS, RBS, …)Creating an OLAP cube with MPM Data WarehouseCreating cost reports from the OLAP cube in excelCreating cost reports from the OLAP cube with reporting services

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Key Session Takeaways

May 16, 2011

By attending this session you will be able to:Understand the MPM data warehouse structureCreate OLAP cubes from MPM data warehouseGenerate reports with excel Generate reports with SQL reporting services Understand basic MDX query

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Overview of Data Warehouse

May 16, 2011

Data Warehouses are designed for storing structured large data for historical information access and reporting.

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Overview of Data Warehouse

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"A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process“ (Bill Inmon, 1990).

Subject Oriented: Data that gives information about a particular subject instead of about a company's ongoing operations.

Integrated: Data that is gathered into the data warehouse from a variety of sources and merged into a coherent whole.

Time-variant: All data in the data warehouse is identified with a particular time period.

Non-volatile: Data is stable in a data warehouse. More data is added but data is never removed. This enables management to gain a consistent picture of the business.

http://www.intranetjournal.com/features/datawarehousing.html

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Overview of Data Warehouse

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A data warehouse is a database used for analyzing overall business strategy rather than routine operations.

A data warehouse database is not a relational database. A relational database stores data of routine operations. A data warehouse database usually store historic data and are suitable for reporting.

Data in an operational database can be transformed and moved into a data warehouse database.

A data warehouse consists of fact tables and dimension tables The most commonly used data warehouse schema architecture are star

schema and snowflake schema.

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Benefits of Data Warehouse

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Data from multiple data sources can be combined to create meaniful information

Ability to extract, load, and transform data into a data warehouse system Designed to handle large data set Inconsistent data can be Identified and and resolved. Data in the data warehouse can be used to create an online analytical

processing (OLAP) cube Ability to slice and dice data in the data warehouse into mutiple dimensions

and present information at diffrent level of granularity. OLAP can be used to apply security at the granularity Users will be able to access information without understanding the data

sources and data structure Data mining can be applied on data in the data warehouse to extract patterns

that can be used to put the company in a better competitive position. Reports with chats can be generated for excutives to analize and help make

critical decisions.

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MPM Data Warehouse StructureTable StructureProject header dataWork breakdown structure (WBS)Resource breakdown structure (RBS)TimeFact/Measures

May 16, 2011

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MPM Data Warehouse Structure

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MPM Data Warehouse StructureProject Tables

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MPM Data Warehouse StructureWBS Table

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MPM Data Warehouse StructureRBS Tables

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MPM Data Warehouse StructureTime

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MPM Data Warehouse StructureFact Table

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Creating an OLAP cube with MPM Data WarehouseDemo

May 16, 2011

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Creating an OLAP cube with MPM Data Warehouse

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1. Launch Business Intelligence Development Studio (BIDs) and create a new Analysis Service Project

2. Create a new data source and use the wizard to connects to the MPM data warehouse

3. Create a new data source view and use the wizard to add tables from the from the MPM data warehouse

4. Use the cube wizard to create a new cube with Project, RBS, WBS, and time dimension.

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Creating cost reports from the OLAP cube in excelDemo

May 16, 2011

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Creating cost reports from the OLAP cube in excel

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1. Launch Microsoft Excel and use the data connection wizard to connect to your OLAP cube

2. Create a PivotTable report with cost data

3. Add charts

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Creating cost reports from the OLAP cube with reporting servicesDemo

May 16, 2011

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Creating cost reports from the OLAP cube with reporting services

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1. Launch Business Intelligence Development Studio (BIDs) and create a new Report Server Project

2. Add a new shared data source using the shared data source wizard

3. Create a cost report

4. Add a chart

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Questions?

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