Strategic and Tactical Information via Data Warehousing Presenter: David Heise Andrews University RP17 - W130 - Wednesday, March :30 PM

RP17: 2 of 33 SCT Summit 1999 IntroductionIntroduction  What this session is about:  Saving your managers from the data flood and the information drought  Who I am:  David Heise, CIO, Andrews University

RP17: 3 of 33 SCT Summit 1999 About Andrews University  Small university of about 3,000 students  In 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

RP17: 4 of 33 SCT Summit 1999 About you  Who is building, or already using, a data warehouse?  Is it (or will it be) in a separate database?  Is it (or will it be) on a separate machine?  Who attended Phil Isensee’s presentation? (GN02 on Monday at 10:00)  Remember to complete the evaluation forms

RP17: 5 of 33 SCT Summit 1999 Presentation Outline 1 What is a Data Warehouse? 2 Why do we need it? 3 How do we get it? 4 Data Warehouse Elements 5 Demonstration of a Business Intelligence Tool

RP17: 6 of 33 SCT Summit What is a Data Warehouse?  The classic 1993 definition by Bill Inmon, “father of data warehousing”  A data warehouse is a: subject oriented subject oriented integrated integrated non-volatile non-volatile time variant time variant  collection of data in support of management’s decisions. 1 of 3

RP17: 7 of 33 SCT Summit What is a Data Warehouse? (continued)  Typical production databases are designed for OnLine Transaction Processing (OLTP)  Data warehouses are designed for a different purpose:  to support ad hoc data analysis, inquiry and reporting by end users, without programmers, interactively and online  This is called OLAP: OnLine Analytical Processing 2 of 3

RP17: 8 of 33 SCT Summit 1999  Mostly for performance reasons, a data warehouse is:  held in a separate database from the operational database,  and usually on a separate machine.  Perhaps more important reasons are:   navigation, ease of use, relationship with business areas 1. What is a Data Warehouse? (continued) 3 of 3

RP17: 9 of 33 SCT Summit 1999 Presentation Outline What is a Data Warehouse? 2 Why do we need it? 3 How do we get it? 4 Data Warehouse Elements 5 Demonstration of a Business Intelligence Tool

RP17: 10 of 33 SCT Summit Why do we need it?  Has a business subject area orientation  Retention analysis  Dean’s / Chair’s management statistics  Student Aid tracking / analysis  Student achievement / outcomes 1 of 10

RP17: 11 of 33 SCT Summit Why do we need it? (continued)  Integrates data from multiple, diverse sources  Banner Oracle database  legacy systems  purchased demographic data  manually collected survey data, etc 2 of 10

RP17: 12 of 33 SCT Summit Why do we need it? (continued)  Allows for analysis of data over time  registration statistics, through registration milestones across years  cohort analysis for retention  revenue and expense comparisons over time 3 of 10

RP17: 13 of 33 SCT Summit Why do we need it? (continued)  Adds ad hoc reporting and inquiry  data organized by business subject area makes navigation easier, more intuitive for business users  ‘point and click’ reporting without programmers 4 of 10

RP17: 14 of 33 SCT Summit Why do we need it? (continued)  Provides analysis capabilities to decision makers  interactive slice and dice, drill down, drill up, etc  “what if” capabilities  graphical data visualization 5 of 10

RP17: 15 of 33 SCT Summit Why do we need it? (continued)  Relieves the development burden on IT  end-user reporting tools mean IT does not have to write programs to answer simple inquiries  questions are answered more readily, information is put to better use in support of decision making 6 of 10

RP17: 16 of 33 SCT Summit Why do we need it? (continued)  Provides improved performance for complex analytical queries  de-normalized star schemas used in data warehouses are better designed for analytical queries than databases designed for OLTP 7 of 10

RP17: 17 of 33 SCT Summit Why do we need it? (continued)  Relieves processing burden on transaction oriented databases  use a specially designed data warehouse, preferably on a separate machine  this isolates production processing from the impact of large, inefficient analytical queries 8 of 10

RP17: 18 of 33 SCT Summit Why do we need it? (continued)  Allows for a continuous planning process  online analysis is available at any time  its interactive nature means different questions can be asked immediately, without reprogramming  there is no need to wait in the development queue, or even in the report production queue 9 of 10

RP17: 19 of 33 SCT Summit Why do we need it? (continued)  Converts corporate data into strategic information  improved decision support results in more timely detection of favorable and unfavorable trends  favorable trends can be capitalized on  early corrective action can be taken for unfavorable trends 10 of 10

RP17: 20 of 33 SCT Summit 1999 Presentation Outline What is a Data Warehouse? 2 Why do we need it? 3 How do we get it? 4 Data Warehouse Elements 5 Demonstration of a Business Intelligence Tool

RP17: 21 of 33 SCT Summit How do we get it? (continued) 1. Be Ready for the Data Warehouse Develop an understanding amongst senior administrators of the potential role of IT and data warehousing in achieving the institution's goals. 2. Choose The Right Project Team 3. Have a Training Strategy Take appropriate training, and/or hire selected consultants. 1 of 4

RP17: 22 of 33 SCT Summit How do we get it? (continued) 4. Choose the Right Architecture Start small, using a phased approach, but within the framework of a system-wide architecture. 5. Have a Project “Mission Statement” Feasibility study Project Charter Project Plan 2 of 4

RP17: 23 of 33 SCT Summit How do we get it? (continued) 6. Show Early Business Benefits Choose strategically important subject areas, (i.e. areas that are linked to the Strategic Plan), that have high visibility and fast return. (remember the rule). 7. Ensure Scalability Evolve the data marts iteratively, constructing the architected data warehouse as you go. 8. Understand the Importance of Data Quality 3 of 4

RP17: 24 of 33 SCT Summit How do we get it? (continued) 9. Be Wary Of Vendor Claims Choose the data repository, data warehousing tools, and desktop tools with care. 10.Use a Proven Data Warehouse Methodology 11.Define and Manage Data Ownership Issues 12.Don’t underestimate the Difficulty of Implementing Change 4 of 4

RP17: 25 of 33 SCT Summit 1999 Presentation Outline What is a Data Warehouse? 2 Why do we need it? 3 How do we get it? 4 Data Warehouse Elements 5 Demonstration of a Business Intelligence Tool

RP17: 26 of 33 SCT Summit Data Warehouse Elements 1.Conferences 2.Consultants 3.Methodologies 4.Design Tools 5.Metadata Repositories 6.Databases 1 of 2

RP17: 27 of 33 SCT Summit Data Warehouse Elements (continued) 7.ETL – Extract/Transform/Load, including cleanse and schedule 8.Ad hoc queries, reports 9.OLAP/Multidimensional data analysis, decision support 10.Data mining/Statistics 11.Decision Analysis 2 of 2

RP17: 28 of 33 SCT Summit 1999 Presentation Outline What is a Data Warehouse? 2 Why do we need it? 3 How do we get it? 4 Data Warehouse Elements 5 Demonstration of a Business Intelligence Tool

RP17: 29 of 33 SCT Summit Demonstration of a BI Tool  This brief demonstration uses PowerPlay, a business intelligence tool from Cognos  Dimensions and facts relevant to Deans and Chairs, and Retention Analysis  Shows how interactive data analysis suggests additional questions, answers the “why” questions

RP17: 30 of 33 SCT Summit 1999 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

RP17: 31 of 33 SCT Summit 1999 QuestionsQuestions “QUESTIONS?”

RP17: 32 of 33 SCT Summit 1999 Contact Details  Contact Details:  David Heise, CIO, Andrews University  Andrews University Data Warehousing   This presentation: 

RP17: 33 of 33 SCT Summit 1999 ResourcesResources  Data Warehousing Buyer’s Guide - TDWI   Larry Greenfield    Data warehousing listserv dwlist    Books, publications, trade journals   TDWI and others publish book lists   DM Review, Intelligent Enterprise (was Datamation)   Training   Vendors and consultants   TDWI, DCI