Operational and Managerial Student Data Needs

1. Operational and Managerial Student Data Needs Frank Wunschel – frank.wunschel@uconn.edu Peter Weinstein – peter.weinstein@uconn.edu University of Connecticut

2. Why a Data Warehouse? • Access to university information • Beyond transactions • Grouping • Aggregation • Correlation • History • Security University of Connecticut

3. Operational and Managerial Dividing Line? • Lists using simple queries • Reports using complex queries • Presentations using charts • Analysis using pivot tables • Thresholds using dashboards University of Connecticut

4. Information Systems CharterJanuary 2000 • Reporting must be accurate, timely, and simple • Implementation of an integrated relational data base from which data can be extracted to position us for the implementation of a data warehouse and institutional reporting capability. • Provide ad hoc reporting tools and on-line query access to data that puts users more in control of accurate and useful information. University of Connecticut

5. PeopleSoft In Practice • Hundreds of PS Reports Delivered • Most setup table Dumps • Absence of needed user reports New reports? Can’t even get some of the old reports • Quick, Check the Project Plan • Reporting not part of the plan • “Outside the Scope”, but very small group of shared resources ultimately “released” back to central UITS. University of Connecticut

6. What to do with Little? • Identify inventory of reports • Get users to tell us what they really need • “A lot of the old stuff isn’t used anyway” • “All the old data error audits aren’t needed” • Inventory result, still plenty of reports needed. University of Connecticut

7. Reporting Responsibility Outside PeopleSoft Team • Develop reports using PS/Query Crystal • Some functional power users just had training • Shift responsibility to them • Unfortunately transactional system performance was barely satisfactory • Couldn’t add additional “load’ to system • Creation of reporting instance deemed “impractical” by PS tech team based on time to load. • Look for alternative reporting data source University of Connecticut

8. Alternative Sources • Data warehouse development • In-house • No resources to develop reports let alone develop data warehouse • Vendor-supplied Alternative • PeopleSoft RDS (ODS then) • Initial impression RDS will meet 65% of need • Hard to assess PS was being careful not to “give away” design University of Connecticut

9. RDS Post Delivery - Good News • Rapid implementation of reporting environment • Many required fields provided in well organized “de-normalized” structure • Data ready to produce “current” data reports. University of Connecticut

10. RDS Post Delivery - Bad News • Rollout Limited by learning curve • Users new to native PS had additional layer of “new” to learn • No selected reporting tool • Less “historical” capability than expected reducing functionality to 30% • Accessible data but still no reports University of Connecticut

11. Responsibility for Reporting • Was not seen as part of PeopleSoft • Centralized UITS • Historically had dedicated reporting team “fed” by user specifications • Many of historical resources went to PeopleSoft • Small group re-allocated by PS got smaller due to early retirement reorganization • UITS position that “New” distributed model moves responsibility to owners. • Responsibility to be distributed among business units? University of Connecticut

12. Distributed Reporting • UITS as provider of reporting environment • Infrastructure, Access • Design, Development of needed Enhancements • Report Repository • Still under consideration • Who provides Training? • Who provides Support? • Who actually writes reports? • System of “liaisons” University of Connecticut

13. Where Are We Today? • Level of Success • Report Readers • Report Writers • Level of Complexity • Reports • Pivot Tables • Charts • Dashboards University of Connecticut

14. Moving Forward • Simplicity • History as it changes • Key performance indicators • Metrics management University of Connecticut

15. Going Back to the Basics • Data Mart Design • Top Ten Reports • Validation • Don’t make me think • Facts • Dimensions • Redundancy University of Connecticut