Strategic and Tactical Strategic and Tactical Information Information

via Data Warehousingvia Data Warehousing

Strategic and Tactical Strategic and Tactical Information Information

via Data Warehousingvia Data Warehousing

Presenter: David HeisePresenter: David Heise

Andrews UniversityAndrews University

RP17 - W130 - Wednesday, March 31 - 1:30 PMRP17 - W130 - Wednesday, March 31 - 1:30 PM

SCT Summit 1999 RP17: 2 of 33

IntroductionIntroductionIntroductionIntroduction

What this session is about:What this session is about: Saving your managers from the data Saving your managers from the data

flood and the information droughtflood and the information drought Who I am:Who I am:

David Heise, CIO, Andrews UniversityDavid Heise, CIO, Andrews University• dheise@andrews.edudheise@andrews.edu• http://http://dheise.andrews.edudheise.andrews.edu• http://www.andrews.edu/itshttp://www.andrews.edu/its

SCT Summit 1999 RP17: 3 of 33

About Andrews UniversityAbout Andrews UniversityAbout Andrews UniversityAbout Andrews University

Small university of about 3,000 studentsSmall university of about 3,000 students In south western corner of MichiganIn south western corner of Michigan We have implemented banner Finance, HR, We have implemented banner Finance, HR,

Student, Alumni and Financial Aid In the process of implementing Web for Student

SCT Summit 1999 RP17: 4 of 33

About youAbout youAbout youAbout you

Who is building, or already using, a data Who is building, or already using, a data warehouse?warehouse?

Is it (or will it be) in a separate database?Is it (or will it be) in a separate database? Is it (or will it be) on a separate machine?Is it (or will it be) on a separate machine? Who attended Phil Isensee’s presentation? Who attended Phil Isensee’s presentation?

(GN02 on Monday at 10:00)(GN02 on Monday at 10:00) Remember to complete the evaluation formsRemember to complete the evaluation forms

SCT Summit 1999 RP17: 5 of 33

Presentation OutlinePresentation OutlinePresentation OutlinePresentation Outline

1 What is a Data Warehouse?1 What is a Data Warehouse?

2 Why do we need it?2 Why do we need it?

3 How do we get it?3 How do we get it?

4 Data Warehouse Elements4 Data Warehouse Elements

5 Demonstration of a Business Intelligence Tool5 Demonstration of a Business Intelligence Tool

SCT Summit 1999 RP17: 6 of 33

1. What is a Data Warehouse?1. What is a Data Warehouse?1. What is a Data Warehouse?1. What is a Data Warehouse?

The classic 1993 definition by Bill Inmon, The classic 1993 definition by Bill Inmon, “father of data warehousing”“father of data warehousing” A data warehouse is a:A data warehouse is a:

• subject orientedsubject oriented• integratedintegrated• non-volatilenon-volatile• time varianttime variant

collection of data in support of collection of data in support of management’s decisions.management’s decisions.

1 of 3

SCT Summit 1999 RP17: 7 of 33

1. What is a Data Warehouse?1. What is a Data Warehouse?(continued)(continued)1. What is a Data Warehouse?1. What is a Data Warehouse?(continued)(continued)

Typical production databases are designed Typical production databases are designed for for OOnnLLine ine TTransaction ransaction PProcessing (OLTP)rocessing (OLTP)

Data warehouses are designed for a Data warehouses are designed for a different purpose:different purpose: to support ad hoc data analysis, inquiry and to support ad hoc data analysis, inquiry and

reporting by end users, without reporting by end users, without programmers, interactively and onlineprogrammers, interactively and online

This is called OLAP:This is called OLAP:OOnnLLine ine AAnalytical nalytical PProcessingrocessing

2 of 3

SCT Summit 1999 RP17: 8 of 33

Mostly for performance reasons, a data Mostly for performance reasons, a data warehouse is:warehouse is: held in a separate database from the held in a separate database from the

operational database, operational database, and usually on a separate machine.and usually on a separate machine.

Perhaps more important reasons are:Perhaps more important reasons are: navigation, ease of use, relationship with

business areas

1. What is a Data Warehouse? 1. What is a Data Warehouse? (continued)(continued)1. What is a Data Warehouse? 1. What is a Data Warehouse? (continued)(continued)

3 of 3

SCT Summit 1999 RP17: 9 of 33

Presentation Outline - 2Presentation Outline - 2

1 What is a Data Warehouse?1 What is a Data Warehouse?

22 Why do we need it? Why do we need it?

3 How do we get it?3 How do we get it?

4 Data Warehouse Elements4 Data Warehouse Elements

5 Demonstration of a Business Intelligence Tool5 Demonstration of a Business Intelligence Tool

SCT Summit 1999 RP17: 10 of 33

2. Why do we need it?2. Why do we need it?2. Why do we need it?2. Why do we need it?

Has a business subject area orientationHas a business subject area orientation Retention analysisRetention analysis Dean’s / Chair’s management statisticsDean’s / Chair’s management statistics Student Aid tracking / analysisStudent Aid tracking / analysis Student achievement / outcomesStudent achievement / outcomes

1 of 10

SCT Summit 1999 RP17: 11 of 33

2. Why do we need it?2. Why do we need it? (continued)(continued)2. Why do we need it?2. Why do we need it? (continued)(continued)

IntegratesIntegrates data from multiple, diverse data from multiple, diverse sourcessources Banner Oracle databaseBanner Oracle database legacy systemslegacy systems purchased demographic datapurchased demographic data manually collected survey data, etcmanually collected survey data, etc

2 of 10

SCT Summit 1999 RP17: 12 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Allows for analysis of data Allows for analysis of data over timeover time registration statistics, through registration statistics, through

registration milestones across yearsregistration milestones across years cohort analysis for retentioncohort analysis for retention revenue and expense comparisons over revenue and expense comparisons over

timetime

3 of 10

SCT Summit 1999 RP17: 13 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Adds Adds ad hocad hoc reporting reporting andand inquiry inquiry data organized by business subject area data organized by business subject area

makes navigation easier, more intuitive makes navigation easier, more intuitive for business usersfor business users

‘‘point and click’ reporting without point and click’ reporting without programmersprogrammers

4 of 10

SCT Summit 1999 RP17: 14 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Provides Provides analysisanalysis capabilities to decision capabilities to decision makersmakers interactive slice and dice, drill down, drill interactive slice and dice, drill down, drill

up, etcup, etc ““what if” capabilitieswhat if” capabilities graphical data visualizationgraphical data visualization

5 of 10

SCT Summit 1999 RP17: 15 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

RelievesRelieves the the developmentdevelopment burden on IT burden on IT end-user reporting tools mean IT does end-user reporting tools mean IT does

not have to write programs to answer not have to write programs to answer simple inquiriessimple inquiries

questions are answered more readily, questions are answered more readily, information is put to better use in information is put to better use in support of decision makingsupport of decision making

6 of 10

SCT Summit 1999 RP17: 16 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Provides Provides improved performanceimproved performance for for complex analytical queriescomplex analytical queries de-normalized star schemas used in data de-normalized star schemas used in data

warehouses are better designed for warehouses are better designed for analytical queries than databases analytical queries than databases designed for OLTPdesigned for OLTP

7 of 10

SCT Summit 1999 RP17: 17 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Relieves processingRelieves processing burden on transaction burden on transaction oriented databasesoriented databases use a specially designed data warehouse, use a specially designed data warehouse,

preferably on a separate machinepreferably on a separate machine this isolates production processing from the this isolates production processing from the

impact of large, inefficient analytical queriesimpact of large, inefficient analytical queries

8 of 10

SCT Summit 1999 RP17: 18 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Allows for a Allows for a continuous planningcontinuous planning process process online analysis is available at any timeonline analysis is available at any time its interactive nature means different its interactive nature means different

questions can be asked immediately, questions can be asked immediately, without reprogrammingwithout reprogramming

there is no need to wait in the there is no need to wait in the development queue, or even in the report development queue, or even in the report production queueproduction queue

9 of 10

SCT Summit 1999 RP17: 19 of 33

2. Why do we need it? 2. Why do we need it? (continued)(continued)2. Why do we need it? 2. Why do we need it? (continued)(continued)

Converts corporate Converts corporate data into strategicdata into strategic informationinformation improved decision support results in improved decision support results in

more timely detection of favorable and more timely detection of favorable and unfavorable trendsunfavorable trends

favorable trends can be capitalized onfavorable trends can be capitalized on early corrective action can be taken for early corrective action can be taken for

unfavorable trendsunfavorable trends

10 of 10

SCT Summit 1999 RP17: 20 of 33

Presentation Outline - 3Presentation Outline - 3Presentation Outline - 3Presentation Outline - 3

1 1 What is a Data Warehouse?What is a Data Warehouse?

2 Why do we need it?2 Why do we need it?

33 How do we get it? How do we get it?

4 Data Warehouse Elements4 Data Warehouse Elements

5 Demonstration of a Business Intelligence Tool5 Demonstration of a Business Intelligence Tool

SCT Summit 1999 RP17: 21 of 33

3. How do we get it? 3. How do we get it? (continued)(continued)3. How do we get it? 3. How do we get it? (continued)(continued)

1. 1. Be Ready for the Data WarehouseBe Ready for the Data WarehouseDevelop an understanding amongst senior Develop an understanding amongst senior administrators of the potential role of IT and data administrators of the potential role of IT and data warehousing in achieving the institution's goals.warehousing in achieving the institution's goals.

2. 2. Choose The Right Project TeamChoose The Right Project Team

3. 3. Have a Training StrategyHave a Training StrategyTake appropriate training, and/or hire selected Take appropriate training, and/or hire selected consultants.consultants.

1 of 4

SCT Summit 1999 RP17: 22 of 33

3. How do we get it? 3. How do we get it? (continued)(continued)3. How do we get it? 3. How do we get it? (continued)(continued)

4. 4. Choose the Right ArchitectureChoose the Right ArchitectureStart small, using a phased approach, but Start small, using a phased approach, but within the framework of a system-wide within the framework of a system-wide architecture.architecture.

5. 5. Have a Project “Mission Statement”Have a Project “Mission Statement”Feasibility studyFeasibility studyProject CharterProject CharterProject PlanProject Plan

2 of 4

SCT Summit 1999 RP17: 23 of 33

3. How do we get it? 3. How do we get it? (continued)(continued)3. How do we get it? 3. How do we get it? (continued)(continued)

6. 6. Show Early Business BenefitsShow Early Business BenefitsChoose strategically important subject areas, (i.e. Choose strategically important subject areas, (i.e. areas that are linked to the Strategic Plan), that have areas that are linked to the Strategic Plan), that have high visibility and fast return. (remember the 80-20 high visibility and fast return. (remember the 80-20 rule).rule).

7. 7. Ensure ScalabilityEnsure ScalabilityEvolve the data marts iteratively, constructing the Evolve the data marts iteratively, constructing the architected data warehouse as you go.architected data warehouse as you go.

8. 8. Understand the Importance of Data QualityUnderstand the Importance of Data Quality

3 of 4

SCT Summit 1999 RP17: 24 of 33

3. How do we get it? 3. How do we get it? (continued)(continued)3. How do we get it? 3. How do we get it? (continued)(continued)

9.9. Be Wary Of Vendor ClaimsBe Wary Of Vendor ClaimsChoose the data repository, data Choose the data repository, data warehousing tools, and desktop tools withwarehousing tools, and desktop tools withcare.care.

10.10. Use a Proven Data WarehouseUse a Proven Data WarehouseMethodologyMethodology

11.11. Define and Manage Data Ownership IssuesDefine and Manage Data Ownership Issues12.12. Don’t underestimate the Difficulty ofDon’t underestimate the Difficulty of

Implementing ChangeImplementing Change

4 of 4

SCT Summit 1999 RP17: 25 of 33

Presentation Outline - 4Presentation Outline - 4Presentation Outline - 4Presentation Outline - 4

1 1 What is a Data Warehouse?What is a Data Warehouse?

2 Why do we need it?2 Why do we need it?

3 How do we get it?3 How do we get it?

44 Data Warehouse Elements Data Warehouse Elements

5 Demonstration of a Business Intelligence Tool5 Demonstration of a Business Intelligence Tool

SCT Summit 1999 RP17: 26 of 33

4. 4. Data Warehouse ElementsData Warehouse Elements4. 4. Data Warehouse ElementsData Warehouse Elements

1.1. ConferencesConferences

2.2. ConsultantsConsultants

3.3. MethodologiesMethodologies

4.4. Design ToolsDesign Tools

5.5. Metadata RepositoriesMetadata Repositories

6.6. DatabasesDatabases

1 of 2

SCT Summit 1999 RP17: 27 of 33

4. 4. Data Warehouse Elements Data Warehouse Elements (continued)(continued)4. 4. Data Warehouse Elements Data Warehouse Elements (continued)(continued)

7.7. ETL – Extract/Transform/Load, includingETL – Extract/Transform/Load, includingcleanse and schedulecleanse and schedule

8.8. Ad hoc queries, reportsAd hoc queries, reports

9.9. OLAP/Multidimensional data analysis,OLAP/Multidimensional data analysis,decision supportdecision support

10.10. Data mining/StatisticsData mining/Statistics

11.11. Decision AnalysisDecision Analysis

2 of 2

SCT Summit 1999 RP17: 28 of 33

Presentation Outline - 5Presentation Outline - 5Presentation Outline - 5Presentation Outline - 5

1 1 What is a Data Warehouse?What is a Data Warehouse?

2 Why do we need it?2 Why do we need it?

3 How do we get it?3 How do we get it?

4 Data Warehouse Elements4 Data Warehouse Elements

55 Demonstration of a Business Intelligence Tool Demonstration of a Business Intelligence Tool

SCT Summit 1999 RP17: 29 of 33

5. Demonstration of a BI Tool5. Demonstration of a BI Tool5. Demonstration of a BI Tool5. Demonstration of a BI Tool

This brief demonstration uses This brief demonstration uses PowerPlayPowerPlay, a business intelligence tool , a business intelligence tool from Cognosfrom Cognos

Dimensions and facts relevant to Dimensions and facts relevant to Deans Deans and and Chairs, and Retention AnalysisChairs, and Retention Analysis

Shows how interactive data analysis Shows how interactive data analysis suggests additional questions, answers suggests additional questions, answers the “why” questionsthe “why” questions

SCT Summit 1999 RP17: 30 of 33

SummarySummary

Some keys to successful data warehousing: Choosing how and where to start

• highly visible and valuable Using a proven methodology, with an

architected approach• have a plan• start small, evolve iteratively

SCT Summit 1999 RP17: 31 of 33

QuestionsQuestions

““QUESTIONS?”QUESTIONS?”

SCT Summit 1999 RP17: 32 of 33

Contact DetailsContact Details

Contact Details:Contact Details: David Heise, CIO, Andrews UniversityDavid Heise, CIO, Andrews University

• dheise@andrews.edudheise@andrews.edu• http://http://dheise.andrews.edudheise.andrews.edu

Andrews University Data WarehousingAndrews University Data Warehousing http://www.andrews.edu/its/dwhttp://www.andrews.edu/its/dw

This presentation:This presentation: http://www.andrews.edu/its/dwhttp://www.andrews.edu/its/dw//AndrewsAndrews/rp/rp17.ppt17.ppt

SCT Summit 1999 RP17: 33 of 33

ResourcesResourcesResourcesResources

Data Warehousing Buyer’s Guide - TDWIData Warehousing Buyer’s Guide - TDWI http://www.dw-institute.comhttp://www.dw-institute.com//

Larry GreenfieldLarry Greenfield http://http://pwp.starnetinc.com/larryg/index.htmlpwp.starnetinc.com/larryg/index.html

Data warehousing listserv dwlist http://http://www.datawarehousing.comwww.datawarehousing.com

Books, publications, trade journals TDWI and others publish book lists DM Review, Intelligent Enterprise (was Datamation)

Training Vendors and consultants TDWI, DCI