5 th Annual Conference on Technology & Standards April 28 – 30, 2008 Hyatt Regency Washington on Capitol Hill The Application of BI in Higher Education John Van Weeren, Product Manager, Datatel, Inc.

Journey to a Culture of Evidence Datatel Copyright Reserved

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

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

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

5 th Annual Conference on Technology & Standards 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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Metric Gauge KPI Status

New Students Enrolled Datatel Copyright Reserved

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

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

5 th Annual Conference on Technology & Standards

5 th Annual Conference on Technology & Standards 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

5 th Annual Conference on Technology & Standards 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

5 th Annual Conference on Technology & Standards 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

5 th Annual Conference on Technology & Standards Dimensional Data Model Fact Table Dimension Star Schema Design Dimension Keys Measures Secondary Information Datatel Copyright Reserved

5 th Annual Conference on Technology & Standards Example Content Fact Areas Dimensions 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 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 Class Schedule Class Schedule Student Term Student Term Class Registration Class Registration Admissions Graduates Faculty Term Faculty Term Student Financials Datatel Copyright Reserved

5 th Annual Conference on Technology & Standards Multi-dimensional Cubes Term Location Age Band Ethnicity Datatel Copyright Reserved

5 th Annual Conference on Technology & Standards 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

5 th Annual Conference on Technology & Standards Making it Real … A lot of times people don’t know what they want until you show them. - Steve Jobs

5 th Annual Conference on Technology & Standards 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

5 th Annual Conference on Technology & Standards Challenges in HE Datatel Copyright Reserved Funding Business Analysts Data Definition Infrastructure

5 th Annual Conference on Technology & Standards Summary for Success Success depends upon previous preparation, and without such preparation there is sure to be failure. - Confucius

5 th Annual Conference on Technology & Standards Questions? Be sure to fill out the survey Thank You! Datatel Copyright Reserved