Overview of the Business Warehouse at the University of Tennessee

1. Overview of theBusiness Warehouseat the University of Tennessee BW Technical Team John Jarrard Jackie Swingle, Jackie Daste, Daniel Dooley (consultant), David Goforth, Ed Johnson, Lynn Sterling December 6, 2000

2. Today’s Presentation • Project Background and Status • Business Warehouse Concepts • The Payoff

3. Two Projects In One • Establish: Legacy Business Warehouse (LBW) IRIS Business Warehouse (IBW)

4. LBW Goal To provide continuing computer access to legacy master and detailed data not planned for conversion to UT’s IRIS system (OLTP, Active R/3)

5. IRIS BW Goal To provide continuing computer access to IRIS financial and human resources data for end user query and decision support processing...

6. Develop IRIS Business Warehouse • Statewide BW Project Team • Identifies data and reporting needs • Technical Support Team • Supports implementation

7. Original Emphasis and Plan • Implement a Legacy Business Warehouse • Address an IRIS Business Warehouse following IRIS Go-Live date of April, 2001

8. New Emphasis and Plan • Cut our teeth on Legacy Business Warehouse • Implement the IRIS Business Warehouse concurrent with the IRIS Go-Live date of April, 2001 • i.e., Management Information System component of IRIS Revised Plan

9. Why the Change? • Continued availability of mainframe • Recognition of robust query and Decision Support System (DSS) capabilities of BW • More effective use of consulting resources

10. New Schedule and Plan • Continue to convert legacy data sources to LBW • Initiate IRIS Business Warehouse Project in November, 2000 for Go-Live with IRIS R/3 • Complete legacy conversion post IRIS Go-Live Go-Live April, 2001

11. Current Status • Significant progress on 3 of 4 legacy data sources planned for LBW • Payroll History • Employee Database • General Ledger Database • Financial Activity • Business Warehouse servers installed • Upgrade to BW 2.0B Completed

12. Current Status (Continued) • Technical Team 2.0B Delta Training Complete • Initial IRIS R/3 InfoCubes Selected for Activation

13. Some Important BW Concepts

14. The Goal: Decision Support • Originally, paper reports produced by programmers • About 1980, copy data from paper reports to spreadsheets • Today, user access to data with analysis and formatting as needed

15. What is a Data Warehouse? • A database used solely for reporting and analysis • Organized by subject area • Integrated • Nonvolatile • Time Variant

16. Data Warehouse: Subject Oriented • Organized into subject areas versus transactions or data entry Athletic Event System HR System Cultural Event System Employee Participation in UT Events Subject Area

17. Data Warehouse: Integrated • Data coming into the warehouse is modified to assign a common coding scheme Athletic Event System HR System Cultural Event System Department code: xxxxxxx Department code: xxxx99.99 Department code: 9999999 Department Code: Common Code or mapping of the various source codes Employee Participation in UT Events Subject Area

18. Data Warehouse: Nonvolatile • Read-only • User can’t write back Transaction Processing (IRIS) Read Write Warehouse (BW) Read

19. Data Warehouse: Time Variant • To support trend analysis • Historical data kept at different levels of detail

20. Business Information Warehouse (BW) • A separate application (add on) • Is independent from SAP R/3. Has its own release and shipment cycle • SAP R/3 runs the day-to-day business • BW is used to support business decisions by providing: • Information analysis • Reporting capabilities

21. Why BW as UT’s Solution? • Integrated with SAP IRIS • Delivered business content • Support using existing knowledge base • BASIS • ABAP • Comprehensive tool set • Extraction • Administration • Query

22. BW Business Content • Goal is to make relevant information available to selected user roles • Assists with: • information deployment • data presentation and analysis • data warehouse management • data extraction and transformation • BW is delivered with many pre-configured and extendable intelligence tools: • 48+ InfoCubes • 166+ queries • 182+ workbooks

23. BW Terminology • Like many software products, SAP uses terminology that may be unfamiliar: • BEx • Query • Operational Data Store • InfoCube • Key Figures • Characteristics • Dimensions

24. BEx Analyzer • An Excel based, interactive environment • Serves as the reporting environment for end users • Allows user to manipulate query output as a document • Used to: • Define queries • Execute queries • Analyze data • Save queries (in workbooks)

25. Queries Available Query • Queries are the instructions used to retrieve data from the warehouse • Users can define their own queries

26. InfoCube • A subset of a data warehouse • Designed to: • Answer specific end-user’s queries • Provide information for specific analysis Available InfoCubes

27. Key Figures • Quantifiable data • Is the lowest level of detail • Example: • non-calculated: Sick Leave Taken Annual Leave Taken Personal Leave Taken • calculated: Total Leave Taken Key Figures | available selected

28. Characteristics • Describes the Key Figures • Typically, data selection criteria such as: • Department • Budget Entity • Fiscal Year Characteristics

29. Dimensions • A logical grouping of characteristics within an InfoCube • An employee dimension might contain: • employee ID • DOB • Academic Rank • Gender Dimensions

30. The Payoff

34. Questions?