The Application of BI in Higher Education John Van Weeren, Product Manager, Datatel, Inc.

1. The Application of BI in Higher Education John Van Weeren, Product Manager, Datatel, Inc.

2. Journey to a Culture of Evidence Datatel Copyright Reserved

3. Operational Effectiveness Admissions Office“In preparation for my 9:00 a.m. meeting, I need an up-to-the-minute count of prospects who have been accepted at our institution for the fall 2008 starting class.” Datatel Copyright Reserved

4. Process Effectiveness Admissions Office“As the new VP of Enrollment Management, I need to measure our success in preparing an offer to a qualified prospect from the time they were targeted to the time the offer letter was sent.” Datatel Copyright Reserved

5. Institutional Effectiveness Admissions Office“Based on our history, where should the student characteristics be at this point in time to ensure that we are on target to meet our shaping goals. So, I need a count of Admit students 30 days after posting our acceptance letters for 2007, 2006, and 2005.” Datatel Copyright Reserved

6. Other Uses of BI • Targeting prospects to improve yield • Optimizing admissions offers • Retention and Intervention • Course offering planning • Optimizing returning student FA awards • Targeting alumni giving • Wealth screening Datatel Copyright Reserved

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8. Status Metric Gauge KPI

9. New Students Enrolled Datatel Copyright Reserved

10. What Are The Tools & Infrastructure? ERP System Reports Microsoft Desktop Tools (Excel, Access, etc.) Microsoft FRx, Reporting Services Analysis Services, ProClarity Performance Point Cognos 8 Reporting Analysis Dashbaording & Scorecarding Oracle Reports Discoverer Enterprise Performance Mgmt Business ObjectsCrystal Reports Web Intelligence Xcelcius, Dashboard Builder Performance Management iStrategy HigherEd Analytics -- ZogoTech – Data Warehousing SAS – SPSS - KXEN Increasing Value Datatel Copyright Reserved

11. ERP ETL Transaction Table Views ETL ETL Operational Data Store and Independent Data Marts Other TransactionSystem Data Data Warehouse What Is The Primary Data Source? Datatel Copyright Reserved

13. What is an ODS? • A separate repository of data from one or more source transaction systems • Data organized for general reporting needs • Level of detail is same as the source transaction systems • Updated on a regular interval • Staging area for data warehouse Datatel Copyright Reserved

14. What is a Data Mart? • A separate repository of data from one or more source transaction systems • Data organized to answer specific business questions in one subject area • Level of detail may be summarized • Updated on a regular interval • Often considered as or part of a data warehouse Datatel Copyright Reserved

15. What is a Data Warehouse? • Kimball – “A copy of transaction data specifically structured for query and analysis.” • Inmon – “… is a subject oriented, integrated, time-variant, and non-volatile collection of data in support of management and the decision making process.” Datatel Copyright Reserved

16. Dimensional Data Model Star Schema Design Dimension Dimension Dimension Dimension Fact Table Dimension Dimension Measures Dimension Keys Secondary Information Dimension Dimension Datatel Copyright Reserved

17. Example Content Dimensions Dimensions Fact Areas Admissions: Application Method Applicant Home State Prior Applicant Ind. Applicant Fin Aid Interest Applicant Housing Interest Recruiting Category Applicant Status Admit Category Applicant SAT Band Applicant HS GPA Band Applicant Age Band Faculty Attributes: Faculty Faculty Rank Highest Education Level Tenured Status Graduates: Graduated Indicator Degree Years to Graduate Admissions Institutional: Term Career/Plan Academic Department Student Term: Academic Level Academic Standing Cohort/Cohort Type Student Term Status FT/PT; Credit Hour Band Class/Grade: Subject/Class Course Level Class Type Grade GPA Band Student Attributes: Student Student Citizenship Student Ethnicity Student Gender Student Geography Student Age Band Student Term Class Schedule Class Registration Faculty Term Graduates Student Financials Datatel Copyright Reserved

18. Term Ethnicity Multi-dimensional Cubes Location Age Band Datatel Copyright Reserved

19. Benefits of this Approach • Flexible organization of data for reporting • Best Performance • Few joins to get related data • Fast indexing • Aggregations done during ETL, not query • Efficient and easy to understand • Facts are in one place, not repeated • Dimensions are reusable with other facts • Accurately represents real life activity Datatel Copyright Reserved

20. Making it Real … A lot of times people don’t know what they want until you show them. - Steve Jobs

24. Related Standards • Data definition • PESC: Core, and all component definitions • College Board: Common Data Set • Data modeling • CWM (Common Warehouse Model) • BPQL (business process query language) • PMML (predictive modeling markup language) • XFRML (extensible financial reporting markup language) Datatel Copyright Reserved

25. Challenges in HE Funding Infrastructure Data Definition Business Analysts Datatel Copyright Reserved

26. Summary for Success Success depends upon previous preparation, and without such preparation there is sure to be failure. - Confucius

27. Questions? Be sure to fill out the survey Thank You! jvw@datatel.com Datatel Copyright Reserved