5 th Annual Conference on Technology & Standards April 28 – 30, 2008 Hyatt Regency Washington on Capitol Hill The Application of BI in Higher

5th Annual Conferenceon Technology & Standards

April 28 – 30, 2008Hyatt Regency Washingtonon Capitol Hill

www.PESC.org

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.”


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.”


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.”



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



b

Metric

Gauge KPI

Status

New Students Enrolled


What Are The Tools & Infrastructure?Operational

EffectivenessProcess

EffectivenessInstitutional

Effectiveness

ERP System Reports

Cognos 8Reporting Analysis Dashbaording & Scorecarding

Microsoft FRx, Reporting Services Analysis Services, ProClarity Performance Point

OracleReports Discoverer Enterprise Performance Mgmt

iStrategy HigherEd Analytics -- ZogoTech – Data Warehousing

Microsoft Desktop Tools (Excel, Access, etc.)

SAS – SPSS - KXEN

Business ObjectsCrystal Reports Web Intelligence Xcelcius, Dashboard Builder Performance Management

Increasing ValueDatatel Copyright Reserved

What Is The Primary Data Source?

Operational Data Store and Independent Data Marts

Transaction Table Views

Other TransactionSystem Data

ERP

Data WarehouseDatatel Copyright Reserved



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



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



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.”



Dimensional Data Model

Fact TableFact Table

DimensionDimension

DimensionDimension

DimensionDimension

DimensionDimension

DimensionDimension

DimensionDimension

DimensionDimension

DimensionDimension

Star Schema Design

DimensionKeys

Measures

SecondaryInformation



Example ContentFact Areas DimensionsDimensions

Admissions:Application MethodApplicant Home StatePrior Applicant Ind.Applicant Fin Aid InterestApplicant Housing InterestRecruiting CategoryApplicant StatusAdmit CategoryApplicant SAT BandApplicant HS GPA BandApplicant Age BandFaculty Attributes:FacultyFaculty RankHighest Education LevelTenured StatusGraduates:Graduated IndicatorDegreeYears to Graduate

Institutional:TermCareer/PlanAcademic Department Student Term:Academic LevelAcademic StandingCohort/Cohort TypeStudent Term StatusFT/PT; Credit Hour BandClass/Grade:Subject/ClassCourse LevelClass TypeGradeGPA BandStudent Attributes:StudentStudent CitizenshipStudent EthnicityStudent GenderStudent GeographyStudent Age Band

ClassSchedule

ClassSchedule

StudentTerm

StudentTerm

ClassRegistration

ClassRegistration

AdmissionsAdmissions

GraduatesGraduates

FacultyTerm

FacultyTerm

Student FinancialsStudent

Financials



Multi-dimensional Cubes

Term

Lo

cati

on

Age BandEthnicity



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



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

- Steve Jobs


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)



Challenges in HE


Funding

Business Analysts

Data Definition

Infrastructure


Summary for SuccessSuccess depends upon previous preparation, and without such preparation there is sure to be failure.

- Confucius


Questions?

Be sure to fill out the survey

Thank You!

[email protected]


Documents

5 th Annual Conference on Technology & Standards April 28 – 30, 2008 Hyatt Regency Washington on Capitol Hill The Application of BI in Higher