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Care and Feeding of a Data Warehouse

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1 Care and Feeding of a Data Warehouse
Mary Louise Powers Lehigh University

2 SCT Banner® Technical Environment
All SCT Banner modules installed All ‘Web for’ products installed AIX/Unix, Oracle 8i Maintained by Enterprise Systems (ESI)

3 Project Background Request for a data warehouse from Institutional Research (IR) Strategic decision support Trend analysis Efficiency and accuracy Single institutional data source

4 Project Background Warehouse definition Time slice, Pre-defined events
Strategic, not transactional Not a Data Mart for operational reporting Direct / indirect customers Data, not reports

5 Project Scope Design and implementation from Spring 2001 to Fall 2002
Graduation back to 1992 Enrollment/Registration from Fall 2001 Primary reporting source for IR

6 Design Focused on enrolled students, courses, graduation
Reporting needs Business processes Technical interest in Dimensional Model and Star Schema

7 Star Schema

8 Design High level technical design
Translated internal processes into schema Allowed for implementation of flat tables Stop gap measure Supporting data from Admissions & Financial Aid


10 Software Requirements
Extraction, translations, cleansing Loading and warehouse table builds Creation of summary tables and views SCT Banner Executive-Self Service (WFE) Data Warehouse Executive Briefing Center Administrative interface

11 Production Environment
Three databases SCT Banner Production “Stage” (copy of SCT Banner Production) Built from Banner export Provides “snapshot” of Banner at critical point in time – data is frozen Limited access Data Warehouse

12 Production Operations
Enrollment / Registration / Graduation extracts Enrollment/Registration Events: 10th day census Midterm census Last day of class Close of term

13 Production Operations
Pre-export audit reporting – SCT Banner production Export of SCT Banner production database Create Stage database from export (can be refreshed at any point in time)

14 Production Operations
Pre-extract audit reporting – Stage Clean up of Stage database Synchronize of Stage and Banner corrections Archive corrected copy of Stage Audit trail Run warehouse maintenance process

15 Customizations / Enhancements
Challenges Data quality Time involvement Getting accurate specifications Post Refresh Process

16 Administering / Managing Production Operations
Manage events processing SCT Luminis 3 Portal – Calendar and task list Operations Who runs the warehouse Support and troubleshooting Security Request Tracking System

17 Technical Infrastructure maintenance Source code housekeeping
Archiving processes WFE upgrade Oracle upgrades Optimize Stage database creation

18 Documentation Metadata Preliminary stage Quest Software - Toad ®
Common Lehigh definitions

19 Documentation

20 Work in Progress You are never done Data retention requirements - TBD
Data integrity issues Potential for implementation of other areas Changing business perspectives (New VP’s, etc)

21 Conclusion On going challenges Benefits Complexity of the system
Timing and synchronization Lehigh’s data quality requirements Benefits Primary data source for IR Ease of use for historical reporting Stability of data

22 References Adamson, C. & Venerable, M. (1998) Data Warehouse Design Solutions. John Wiley & Sons, Inc. Dodge, G. & Gorman, T. (1998) Oracle8 Data Warehousing, A Hands on Guide to Designing, Building, and Managing Oracle Data Warehouses. John Wiley & Sons, Inc. Kimball, R. (1996) The Data Warehouse Toolkit. John Wiley & Sons, Inc.

23 Questions?

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