From Data Warehouse to Business Intelligence: The Michigan Journey John Gohsman University of Michigan Sean Mallin iStrategy Solutions Presenters:

Michigan Facts Three campuses –Ann Arbor (40,000 students, 23,000 faculty/staff) –Dearborn & Flint (12,000 students, 1,800 faculty/staff) Health System –Includes: Medical School, 3 hospitals, 30 health centers and 120 outpatient clinics (13,000 total employees) Financial Picture –Annual Budget >$4 Billion (10% from State of Michigan) –$823M research funding per year (NIH 47%, NSF 9%, DOD 8%) –Endowment: $6 billion Michigan values its highly decentralized nature –“Coordinated autonomy”

iStrategy Facts Sean to complete…

Presentation Outline The Data Warehouse Foundation Moving to Business Intelligence Demonstrations What’s Next

The 80s

1980s Source: OTLP Tools: PL/1, ASI/Inquiry Users: Programmers, Power (10’s) Exec Decision Support Management Operational INFORMATIONMATURITYINFORMATIONMATURITY FIN DEVL HR STU PUR

The 90s

Established Data Administration –Strategic Data Planning –Policy, Guidelines (Data as an Asset) –Governance (Stewards/Managers, not Owners) –Data Modeling Services, Naming Conventions Built Data Warehouse –Financials, Human Resources, Student, Fundraising –Relational approach for flexibility 1980s Early 1990s Source: Oracle Data Warehouse Tools: GQL Users: Power (100’s)

Strategic Data Plan published –Replace all legacy systems –Need new technical platform Bought PeopleSoft ERP Commit to replace each data set 1980s 1995 Source: Oracle Data Warehouse Tools: GQL Users: Power (~ 1,000) Users: Power (~ 1,000)

1998 –Developed DW principles and vision –Student Recruiting and Admissions –Financials Financials delivers majority of reports via DW 2000 –Rest of Student Administration 2001 –Human Resource Management System 1980s Source: ODS and Oracle Data Warehouse Tools: PS Query and Business Objects Users: Power and Casual (~2000)

2000 and Beyond

Execs wonder about ERP ROI? –Operational efficiency but… Are we leveraging data for improved decision-making Units making progress –M-Dash and M-Stat in Medical School (Xcelsius) –UHR defines and delivers metrics; also pushes key info via /Excel Establish Advisors on Information Management Strategy (AIMS) –Develop strategy 1980s 2005 Source: ODS and Oracle Data Warehouse Tools: PS Query and BusinessObjects Users: Power and Casual (~2000)

Presentation Outline The Data Warehouse Foundation Moving to Business Intelligence Demonstrations What’s Next

AIMS delivers BI Strategy –Leverage BI Framework –(use framework slide?) –Issues Lack of campus readiness or awareness Silo approach Lack of applications Complicated data structures Limited tools Missing infrastructure 1980s 2006 Source: ODS and Oracle Data Warehouse Tools: PS Query and BusinessObjects Users: Power and Casual (~2000)

UM BI Framework Adapted from Gartner Research Data Sources FIN StudentHR Devl Unit- specific Infrastructure Data Warehouse, ODS, ETL, Data Quality, Metadata, Data Marts Applications and Functionality Ad hoc query/reporting, standard/canned reporting, statistical analysis, data mining, predictive modeling, presentation/alert/push technology Process Performance mgt, methodology, education Strategy Tools BI end user tools, BI developer tools, XCelsius, OutlookSoft Everest Users Organization Skills, BI Competency Community

AIMS recommendations –Build awareness via BI Community BI Council –BI Community of Experts, Communications, Data, Training/Methods –Address user segments; increase market Power (1500), operational (8000), casual/guided analysis (>10,000) –Increase tools portfolio, infrastructure Browser-based, solutions for execs, managers, etc. –Improve data structures Aggregate, derive = dimensional, OLAP Incorporate into Administrative Systems Strategic Plan 1980s 2006 Advisors on Information Management Strategy (AIMS) Business Intelligence Council (BIC) Training & Methods Subgroup Communi- cations Subgroup Data Subgroup Data Subgroup BI Community of Experts (BICE)

Web Reporting OperationalPower ToolsData from Multiple Sources Entry Points

Vision

Create BI Council and subgroups Created annual BI Awards Parallel progress while campus readiness improves –Decision to upgrade Business Objects and acquire site license –Decision to build web reporting solution for guided analysis (internal controls, PI reports) –Decision to acquire cubes for Financials and partner to develop HR metrics cube –Research archive/purge, ETL/CDC tools 1980s Source: ODS, Oracle DW, SQL Server Tools: PS Query, Business Objects, Proclarity,.Net Users: Power and Casual (~2000)

Presentation Outline The Data Warehouse Foundation Moving to Business Intelligence Demonstrations What’s Next

iStrategy: HR Metrics

M-Reports

M-Reports Vision M-Reports will deliver business intelligence to users in a customizable user interface Alerts, metrics and personalized reports based on user profile, preferences and role based security Guided analysis through data Data sourced from multiple underlying databases (production, ODS, Data Warehouse, unit data) MAIS and University units can develop and publish content

Presentation Outline The Data Warehouse Foundation Moving to Business Intelligence Demonstrations What’s Next

Creating a BI Organization Increase size of team Expand mission, increase functions –Add Analytical skills –Increase Application Development –Enhance BI Community –Increase Consulting and Training –Enhance Data Administration –Improve Data Set Development –Increase Tools Support

Deliver More Solutions More cubes, dimensional models Broad content in M-Reports Dashboards (KPIs, personalized thresholds) Push (reports, alerts) Predictive Analytics Workflow Process Management

Build a solid foundation Deliver to campus –Provide different data structures and a portfolio of tools to meet different needs Engage campus –Executive leadership –Community awareness and understanding Make progress at all levels of framework 1980s Summary Source: ODS, Oracle DW, SQL Server Tools: PS Query, Business Objects, Proclarity,.Net Users: Power and Casual (15,000)

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Microsoft M-Reports Proclarity BusinessObjects ETL HE (PeopleSoft) FIN (PeopleSoft) Development eResearch Reporting Copy (PeopleSoft) Enterprise Data Warehouse Oracle HR Fin GLStu DevlPR BI Tools ETL iStrategy FIN iStrategy HR Internal Cubes U-M Business Intelligence Overview

Legacy data sets M-Pathways data sets Business Objects M-Pathways Oracle 10g Data Warehouse Oracle 10g Predefined Reports Ad Hoc Queries Extract/Transform using SQR HE PeopleSoft (Ver. 9) FIN PeopleSoft (Ver. 8.8) Load BI Tools BusinessObjects XIR2 WebI and Infoview Relational Data Warehouse Environment

U-M Star Schemas/Cubes: M-Reports Single Purpose Star Schemas Internal Controls Staging BI Tools Sources Multi Purpose Star Schemas iStrategy Staging BI Tools Sources

M- Pathways M-Reports Design Schema (Temp Pay Example) Using MS Reporting Services for Grids and Graphs. Need to decide about additional sw. Assumption: No direct access to LCC from outside an application (including UI) Web services are very simplistic BLL Components contain all business logic DAL Components build and pass SQL/MDX Commands Cubes vs. Relational Security Layer Web Services Business Logic Layer Data Access Layer Data Bases M-Reports Portal Non M-Reports UI External Customers Security Component (written in-house) Temp Pay Get Temp Pay Get Temp Pay By Funding Dept M-Reports BLL Get Distinct Campus Temp Pay BLL Get Temp Pay Get Temp Pay By Funding Dept M-Reports DAL Build General Parms Select Distinct Campus Temp Pay DAL Select Temp Pay Future