Best Practices in Higher Education Student Data Warehousing ForumBest Practices in Higher Education Student Data Warehousing Forum Northwestern UniversityNorthwestern University

October 20-21, 2003October 20-21, 2003

Building Data Warehouse at RensselaerBuilding Data Warehouse at Rensselaer Ora Fish

Rensselaer Polytechnic Institute

AgendaAgenda

BackgroundBackground Development MethodologyDevelopment Methodology Rollout Strategy Rollout Strategy Summary Status – where are we nowSummary Status – where are we now Benefits Benefits Lessons LearnedLessons Learned Demonstrations of the Financial Analysis Demonstrations of the Financial Analysis

Data Mart – Executive Information Systems Data Mart – Executive Information Systems Q & AQ & A

Facts about RensselaerFacts about Rensselaer (RPI) (RPI)

““We are the first degree granting We are the first degree granting technological university in the English-technological university in the English-speaking world”speaking world”Research UniversityResearch UniversityTotal Students Total Students 9,1459,145 Graduates – 4,006Graduates – 4,006 Undergraduates – 5,139Undergraduates – 5,139Faculty - 450Faculty - 450

Founded in 1824 by Stephen Van Rensselaer

Facts about PresenterFacts about Presenter

Bachelor in Math and Computer Science Bachelor in Math and Computer Science from Tel-Aviv University, Israelfrom Tel-Aviv University, IsraelMBA from RPIMBA from RPI23 years in system implementation and 23 years in system implementation and software development in variety of software development in variety of technical and management positionstechnical and management positionsOver 8 years in RPIOver 8 years in RPIInvolved with the Data Warehouse for the Involved with the Data Warehouse for the past five – six years past five – six years

Fundamental ProblemFundamental Problem

Operational systems are not designed for Operational systems are not designed for information retrieval and analytical information retrieval and analytical processingprocessing

First attempt to fund DW First attempt to fund DW project Failsproject Fails

Reasons for failing funding in Fall of 1997 :Reasons for failing funding in Fall of 1997 :

TimingTiming

ExpectationExpectation

Lucking business sponsorLucking business sponsor

Analytical culture Analytical culture

What does it What does it reallyreally means?? means??

Second Attempt to Fund DW Second Attempt to Fund DW Project is SuccessfulProject is Successful

Spring 2000 - The following changes had occurred:Spring 2000 - The following changes had occurred:

Timing – Banner does not addresses reporting; Timing – Banner does not addresses reporting; Views are too slow to be usedViews are too slow to be used

Organizational changes (New President, CIO)Organizational changes (New President, CIO)

Performance Planning Performance Planning

We have build a PrototypeWe have build a Prototype

Buy-in ProcessBuy-in Process

Demonstrate to those who need this Demonstrate to those who need this information desperately information desperately

The word is outThe word is out

From the CIO to the committees to the From the CIO to the committees to the cabinetcabinet

Buy-in ProcessBuy-in Process

We are prepared to address:We are prepared to address:

Budgets Budgets

Timelines Timelines

We are ready with the white paperWe are ready with the white paper to to communicate the key components communicate the key components (iterative development under overall (iterative development under overall planning, business users involvement, planning, business users involvement, meta data, approaches)meta data, approaches)

The Fundamental GoalThe Fundamental Goal

The fundamental goal of the Rensselaer Data The fundamental goal of the Rensselaer Data Warehouse Project is to integrate Warehouse Project is to integrate administrative data into a consistent administrative data into a consistent information resource that supports planning, information resource that supports planning, forecasting, and decision-making processes forecasting, and decision-making processes at Rensselaer.at Rensselaer.

Development methodologyDevelopment methodology

Phase I – Building FoundationPhase I – Building Foundation

Phase II – Iterative Process of Building Phase II – Iterative Process of Building Subject Oriented Data MartsSubject Oriented Data Marts

On going Operations: Support and On going Operations: Support and Training; Maintenance and Growth Training; Maintenance and Growth

Rolling ImplementationRolling Implementation

Infrastructure Planning/StaffingSoftwareDatabase/HardwareProduction Platform

Policy Data PolicyDatamarts Finance/Research Req

Position Cntrl/LaborHuman ResourcesEnrollmentGrad Financial AidUndergrad Fin AidContracts & GrantsAdmissions Pipeline

Operations SupportSoftware UpgradeDatabase UpgradeHardware Growth

RolloutDev & Test

FY02 FY03 FY04 FY05

Phase I – Building FoundationPhase I – Building Foundation

Organizational StructureOrganizational Structure

Project framework and high level Project framework and high level planplan

Building Building TechnicalTechnical Infrastructure Infrastructure

Develop Data Policies and Develop Data Policies and ProceduresProcedures

HiringHiring

Project Organizational StructureProject Organizational Structure

Sponsorship Group

Steering Committee

Implementation groups

Progress report

Forming Implementation groups; Defining scope and deliverables

Data Warehouse Group

Implementation issues

Business Intelligence Selection CommitteeFinancial Analysis Implementation GroupFinancial Analysis Reviewer GroupData Policy Group

Project FrameworkProject Framework

High Level AnalysisHigh Level Analysis

Prioritization processPrioritization process

Hire and train staff, Choose Hire and train staff, Choose consultantconsultant

Establish communication Establish communication channels channels (web site, newsletters, kickoff (web site, newsletters, kickoff event…) event…)

High Level Analysis and High Level Analysis and Prioritization processPrioritization process

CONSTITUENCIES

BUSINESS PROCESSES

Enrollment Analysis X X X X X X X X

Student Pipeline Analysis X X X X X

Faculty Workload Assessment X X X X X X

Financial Analysis X X X X

Contract and Grants Analysis X X X X X

Proposal Pipeline Analysis X X X X

Financial Analysis - Research X X X X X X

Graduate Financial Aid X X X

Alumni Demographics and Tracking X X X X X X

Alumni Contact Management X X

Human Resources X X X X X

Facilities Management X X X

Prioritization ProcessPrioritization Process

Value toRennselaer

Feasibility HighLow

High

FM

HR

PP

GF

AC

FW

FR SP

AD

EA

FA

CG

Brio PortalAIX

BrioODS/JF Node

production data warehouse machineAIX 4-CPU 4GB RAM

end-user machines

banner reportinginstance (clone)AIX

webserverAIX

BrioSharedMetadata

InformaticaRepository

metadata

BannerReportingInstance

Oracle 9i

transactional systems

• extraction• transformation• modeling• loading

• central repository• subject-based data marts• metadata• conformed dimensions

• user-facing applications• report generation• subject-based data cubes• data mining

• business intelligence• decision-support• OLAP• querying• reporting

DATA SOURCES DATA ACQUISITION DATA WAREHOUSE DATA DELIVERY DATA CONSUMPTION

DWDB(targets)

Oracle 8i[DWDB]

InformaticaPowerCenterETL Server

BrioInsight

analysts

Brio Portal

BrioWebClient

MicrosoftExcel

analysts

banner productionAIX

Banner

Oracle 9i[PROD]

Dash Boards

contentViewers

Building Technical ArchitectureBuilding Technical Architecture

Technical Architecture InventoryTechnical Architecture Inventory

ERP – Banner from SCTERP – Banner from SCT

ETL – Power Center from InformaticaETL – Power Center from Informatica

Data Base – Oracle 8iData Base – Oracle 8i

Models – Star schemas with conformed Models – Star schemas with conformed dimensionsdimensions

Web Front end tools – Brio, Dash BoardsWeb Front end tools – Brio, Dash Boards

Desktop Front End tools – Brio, ExcelDesktop Front End tools – Brio, Excel

Data Security, Privacy and Access PolicyData Security, Privacy and Access Policy

Can be defined as striking the “right” balance between Can be defined as striking the “right” balance between data security/privacy and data accessdata security/privacy and data access

Value of data is increased through widespread access Value of data is increased through widespread access and appropriate use, however, value is severely and appropriate use, however, value is severely compromised by misinterpretation, misuse, or abusecompromised by misinterpretation, misuse, or abuse

This policy considers security and privacy paramountThis policy considers security and privacy paramount

Key oversight principle:Key oversight principle: Cabinet members, as individuals, are responsible for overseeing Cabinet members, as individuals, are responsible for overseeing

establishment of data management policies, procedures, and establishment of data management policies, procedures, and accountability for data governed within their portfolio(s), subject accountability for data governed within their portfolio(s), subject to cabinet review and CIO approvalto cabinet review and CIO approval

Security& Privacy

Access& Use

Phase IIPhase IIComponents of Building Subject Components of Building Subject

Oriented Data MartsOriented Data MartsDefining Scope and TimelinesDefining Scope and TimelinesModelingModelingDevelopmentDevelopmentRecord MetadataRecord MetadataLocal TestingLocal TestingCore Administration TestingCore Administration TestingDesign and Develop SecurityDesign and Develop SecurityCore Administration live in ProductionCore Administration live in ProductionFront-End development for the campusFront-End development for the campusCampus RolloutCampus Rollout

JAD & RAD Approach

Defining ScopeDefining Scope

Identify Constituency Identify Constituency

Detailed Requirements Definitions Detailed Requirements Definitions

Analyze Data Sources / raise issuesAnalyze Data Sources / raise issues

Define Scope Define Scope

Acceptance/Project ReviewAcceptance/Project Review

Develop and approve specific security Develop and approve specific security policypolicy

ModelingModeling

Subject-based data marts

Star Schemas

Conformed dimension

Graduate Financial Aid Data ModelGraduate Financial Aid Data ModelOne row per student per term per support typeOne row per student per term per support type

Graduate SupportSnapshot

Student Dimension

Fund Dimension

OrganizationDimension

Account Dimension

Program Dimension

Activity Dimension

Tuition Assistance AmtTuition Assistance Fees AmtTuition Assistance Disb. AmtTuition Assistance Fees Disb. AmtTuition Assistance Expensed AmtDegree Completion AmtDegree Completion Disb. AmtStipend Amt

Student Key

Academic Term KeyPrim Program Major Grp KeySec Program Major Grp KeyStudent keyStudent Cohort KeyClass KeyFund KeyOrg KeyAccount KeyProgram KeyActivity KeyGrant KeyStudent Faculty Advisor Key

Fund Key

Org Key

Account Key

Program Key

Activity Key

Academic DegreeBridge Dimension

Student Degree Key

ACADEMIC TERMDIM

Academic Term Key

Class Key

Student CohortBridge

Student Cohort Key

Grant Dimension

Grant Key

Student FacultyAdvisor Bridge

Student Faculty AdvisorKey

Class Dimension

Cohort Key

Faculty Advisor Key

Graduate Support Snapshot

GFA Support Type Key

GFA Support TypeDimension

Student Enrollment Model – one Student Enrollment Model – one row per enrolled student per term row per enrolled student per term

Student EnrollmentSnapshot

Student Dimension

Class Dimension

Student countMatriculated countCredit Hours RegisteredCredit Hours AttemptedCredit Hours EarnedOverall GPATerm GPATuition Amt ChargedTuition Fees ChargedTuition Amount BilledTuition Fees Billed

Student Key

Academic Term KeyPrim Program Major Grp KeySec Program major Grp KeyStudent keyStudent Cohort KeyClass KeyStudent Faculty Advisor Key

Class KeyAcademic ProgramBridge Dimension

Student AcademicProgram Key

Academic TermDimension

Academic Term Key

Student FacultyAdvisor Bridge

Student Faculty AdvisorKey

Student CohortBridge

Student Cohort Key

Faculty Advisor Key

Cohort Key

Student Enrollment Snapshot

Summary GFA ModelSummary GFA Modelone row per graduate student per termone row per graduate student per term

Student EnrollmentSnapshot

Student Dimension

GFA STATUS

Student countIRA countERA countTA countFellowship countScholarship countSelf supported countCumulative terms enrolledCumulative terms affiliatedCurrent Tuition Amt ChargedCurrent GFA Stipend Amt

Student Key

Academic Term KeyPrim Program Major Grp KeySec Program major Grp KeyStudent keyStudent Cohort KeyClass KeyStudent Faculty Advisor Key

GFA KeyPrimary ProgramDimension

Student AcademicProgram Key

Academic TermDimension

Academic Term Key

Student FacultyAdvisor Bridge

Student Faculty AdvisorKey

Primary FundingSource

Funding Key

Faculty Advisor Key

Graduate Student Count Enrollment Snapshot

Development - ETLDevelopment - ETL

Data Staging Design and DevelopmentData Staging Design and Development

Design & Develop Aggregation ProcessDesign & Develop Aggregation Process

Develop Data Quality Assurance Develop Data Quality Assurance ProcessesProcesses

User testing testing and testing User testing testing and testing …..…..

Note: the Data Warehouse serves the needs Note: the Data Warehouse serves the needs for ad-hoc analysis and reporting of various for ad-hoc analysis and reporting of various groups of usersgroups of users Testers are: Deans, Cabinet, Financial Testers are: Deans, Cabinet, Financial

Managers, Core Administration offices…Managers, Core Administration offices… Testing period is an opportunity to create Testing period is an opportunity to create

more definitions, groupings, and more definitions, groupings, and transformations…transformations…

Identify Testing Candidates - key users identified Identify Testing Candidates - key users identified in the scopein the scopeTrain Users in Brio Train Users in Brio Transfer of Knowledge from Developer to Transfer of Knowledge from Developer to Testing GroupTesting Group Sample ReportsSample Reports Document Data Mart Description Document Data Mart Description Document Standard Naming Conventions Document Standard Naming Conventions Document Common Uses for Each Star SchemaDocument Common Uses for Each Star Schema

User Set-Up User Set-Up

Prior To User Acceptance TestingPrior To User Acceptance Testing

Testing sessionsTesting sessions

Allocating time slotsAllocating time slots

Targeting – aiming to produce resultsTargeting – aiming to produce results

Verifying that the models do address the Verifying that the models do address the needneed

Great opportunity to bridge diverse groups Great opportunity to bridge diverse groups

Defect/Enhancement LogDefect/Enhancement Log

Date ReportedDate ReportedPriority Level (i.e. High, Medium, Low)Priority Level (i.e. High, Medium, Low)Defect and/or Enhancement DescriptionDefect and/or Enhancement DescriptionUser Reporting Defect and/or Enhancement User Reporting Defect and/or Enhancement Defect/Enhancement Status Defect/Enhancement Status

IncomingIncoming PendingPending Work In ProgressWork In Progress User Acceptance TestingUser Acceptance Testing ClosedClosed Focus GroupFocus Group

Assigned ToAssigned ToResolutionResolutionUser Assigned To Test ResolutionUser Assigned To Test Resolution

Recording MetadataRecording Metadata

User driven effortUser driven effort

Stored in Informatica repositoryStored in Informatica repository

Accessed via BrioAccessed via Brio

Development - Securing Data Development - Securing Data MartsMarts

Ensure that the subject oriented Data Ensure that the subject oriented Data Policy is definedPolicy is defined

Technically feasibleTechnically feasible

ApprovedApproved

Build Security Front End applicationBuild Security Front End application

Data Security optionsData Security options

Securing schemasSecuring schemas

Securing facts onlySecuring facts only

Securing dimensions onlySecuring dimensions only

Securing both facts and dimensionsSecuring both facts and dimensions

Nuts and Bolts of the Data Base Nuts and Bolts of the Data Base Security Security

Data Base security applies to Data Base security applies to all individualsall individuals given either given either direct accessdirect access to the warehoused data or given permissions to to the warehoused data or given permissions to processprocess Brio dynamic Brio dynamic reportsreports

Organization Managers And Financial Managers will have access to Organization Managers And Financial Managers will have access to the warehoused the warehoused financial financial data based on the following criteriadata based on the following criteria

All financials posted against that OrgAll financials posted against that Org All funds listing that Org as a home Org All funds listing that Org as a home Org (in cases of research funds, this (in cases of research funds, this

defines where the research is brought into)defines where the research is brought into) All funds listing the PIs (or the Financial Manager) associated with that All funds listing the PIs (or the Financial Manager) associated with that

Org as fund financial managers. Org as fund financial managers. (Resolves the Multi-disciplinary issue)(Resolves the Multi-disciplinary issue) All funds and orgs listing that Org as a predecessor in either one of the All funds and orgs listing that Org as a predecessor in either one of the

above three cases.above three cases. Administrative role: Individuals might be granted Administrative role: Individuals might be granted accessaccess to additional to additional

funds and org based on funds and org based on their needs and their role within Rensselaertheir needs and their role within Rensselaer. .

Position Control and Labor Data Position Control and Labor Data Policy Overview Policy Overview

Already have access to Labor data in BannerAlready have access to Labor data in BannerCompleted DW trainingCompleted DW trainingAccess to Budgets and Labor data for all Funding, Access to Budgets and Labor data for all Funding, Employees, or Positions owned by their Organization Employees, or Positions owned by their Organization as following:as following:

Funding:Funding: All actual and budgeted labor expenses posted All actual and budgeted labor expenses posted against their Organizationagainst their Organization

Employees:Employees: All actual and budgeted labor expenses All actual and budgeted labor expenses associated with the Employees reporting to their Organization associated with the Employees reporting to their Organization within the timeframes of the employees’ employment in the within the timeframes of the employees’ employment in the Organization.Organization.

Positions:Positions: All actual and budgeted labor expenses associated All actual and budgeted labor expenses associated with Positions owned by their Organizations.with Positions owned by their Organizations.

All of the above within their Organizations’ hierarchy.All of the above within their Organizations’ hierarchy.

HR Security Policy OverviewHR Security Policy Overview Access to Employee Information Access to Employee Information

Enrollment and Graduate Financial Enrollment and Graduate Financial Aid Data Policy OverviewAid Data Policy Overview

Access to aggregate data is based on Access to aggregate data is based on “need to know”“need to know”Access to student identifiable information Access to student identifiable information is restricted as following:is restricted as following: Sponsoring graduate students Sponsoring graduate students Major Major AdvisementAdvisement Central administration/management of the Central administration/management of the

University University

Access to Undergraduate Financial Access to Undergraduate Financial AidAid

Restricted to very few positions within:Restricted to very few positions within:

President OfficePresident Office

Institutional ResearchInstitutional Research

Students Records and Financial ServicesStudents Records and Financial Services

Financial Aid OfficeFinancial Aid Office

Development – Front EndDevelopment – Front End

Dash Board Design and Development – Dash Board Design and Development – Joint effort with Core AdministrationJoint effort with Core Administration

Training testing groups in BrioTraining testing groups in Brio

Develop first version of Brio dynamic Develop first version of Brio dynamic documents and publish via Portal – Joint documents and publish via Portal – Joint effort with Core Administrationeffort with Core Administration

Campus RolloutCampus Rollout

Defining roles and responsibilities Defining roles and responsibilities

Who will have initial access to whatWho will have initial access to what

Develop Roll out strategyDevelop Roll out strategy

Setting expectationsSetting expectations

Designing and carrying out Training Designing and carrying out Training ProgramsPrograms

CommunicateCommunicate

Executive briefingsExecutive briefings

During TrainingDuring Training

Campus orientationsCampus orientations

Wed siteWed site

Any possible vehicle ….Any possible vehicle ….

Initial Tiered Access – Who will Initial Tiered Access – Who will have access to whathave access to what

Dash Board

Informationpublished

In Brio documents

Data in the Warehouse

Cabinet; Deans; Department Chairs; Center Directors

Finance AdministrationPortfolio Financial Managers

Department Financial Managers

Trai

ning

Hig

h

Low

Brio Products Overview Brio Products Overview (Brio Intelligence)(Brio Intelligence)

Brio Portal

Data Warehouse

Folders, Published Documents, Personalized

Content, Dashboards, ERD

Brio Insigh

t

Each user will have separate Portal and database usernames and passwords. The Portal login provides the user with access to published content based on a security profile. The database login is necessary to

extract data from the Data Warehouse.

Web

Connects to the DW without Portal

Brio Insight User

Brio Desktop User (i.e., Brio Explorer, or

Designer)

Connects to the DW with Insight and Portal via

the Web

Portal and Insight are also

available to Desktop users via the Web

Finance Data Mart

Graduate Financial

Aid

Position Control

Data Mart

Student Enrollmen

t

Other Data Marts

Brio PortalBrio Portal

Allows users to access published documents (e.g., BQYs, Brio manuals, training documents) and personalize their content

Executive Dashboard OverviewExecutive Dashboard Overview

Accessed via the PortalAccessed via the PortalHigh-level, graphical High-level, graphical views of Portfolio-specific views of Portfolio-specific datadataDesigned primarily for Designed primarily for executive use, though executive use, though available to other users available to other users as wellas wellComprised of monthly Comprised of monthly summary data, refreshed summary data, refreshed nightlynightly

Dashboard Help: http://www.rpi.edu/datawarehouse/dw-help-dashboards.html

Campus Rollout AssumptionsCampus Rollout Assumptions

Training is mandatory at all levels.Training is mandatory at all levels. Several levels of training will be offered to campus Several levels of training will be offered to campus

in Brio tools, Data, and Data Policies.in Brio tools, Data, and Data Policies. Joint effort between DW Group and Core Joint effort between DW Group and Core

AdministrationAdministration

Portfolio Financial Managers responsibilities:Portfolio Financial Managers responsibilities: Rollout within PortfolioRollout within Portfolio Training within PortfolioTraining within Portfolio

Data Warehouse Cascaded Data Warehouse Cascaded Rollout StrategyRollout Strategy

1. Core Administration

2. Portfolio Level (Cabinet, Deans, Portfolio Managers)

3. Department Level (Directors, Center Directors, Department Chairs, Department Financial Managers)

4. Other

Training MethodologyTraining Methodology

Primarily Portfolio Financial Managers who will build ad-hoc queries and reports (i.e., Brio documents) from data mart star schemas and meta topics.

Track 2

Track 3

Track 1

Department Financial Managers who will work primarily with pre-built Brio documents.

Brio 101

Brio 101Level 1:

Portfolio/Dept-Specific Pre-Built Docs

Level 1: Data Mart

Basics

Level 2: Advanced

Brio Documents

Designed for Executive users, this track focuses on Dashboards and the Brio Portal.

Dashboard & Portal trainingOne-on-one or small group formatLow

Medium

High

Training

Required

Setting and Communicating Setting and Communicating ExpectationsExpectations

Communicate to Institute ExecutivesCommunicate to Institute Executives Creating an Information RevolutionCreating an Information Revolution Changing cultureChanging culture Top down approach is neededTop down approach is needed Recognize BarriersRecognize Barriers Ask for commitmentAsk for commitment

Recognizing BarriersRecognizing Barriers

People’s resistance to a new toolPeople’s resistance to a new tool

Expectations on information availability and Expectations on information availability and usability for decision making are lowusability for decision making are low

Habit of relying on Central Administration to Habit of relying on Central Administration to provide information, or on their own sources provide information, or on their own sources (many versions of the ‘truth’)(many versions of the ‘truth’)

People will need to acquire new job skillsPeople will need to acquire new job skills

Job expectations will need to changeJob expectations will need to change

How to get there ….How to get there ….

Common Vision:Common Vision:

One version of the truthOne version of the truth

Data Experts across campus and across organizational Data Experts across campus and across organizational boundariesboundariesData Experts:Data Experts: Portfolio Financial Managers or Equivalents will be Portfolio Financial Managers or Equivalents will be

expected to:expected to: access dataaccess data create reportscreate reports perform analysisperform analysis enable/train Portfolio end-users enable/train Portfolio end-users

Training approachTraining approach

Evaluating skill levelsEvaluating skill levels: : Surveys before training Surveys before training

Measuring satisfactionMeasuring satisfaction with training with training program: program: Overall satisfaction with program content is Overall satisfaction with program content is very high: 91% gave the highest survey rating.very high: 91% gave the highest survey rating.

Partnering with HRPartnering with HR – – The DW training was The DW training was included in the appropriate Performance Evaluations / included in the appropriate Performance Evaluations / Job Descriptions and course offeringsJob Descriptions and course offerings

Measuring access levelsMeasuring access levels – generating log files – generating log filesUtilizing Web Utilizing Web – self help, registration, – self help, registration, communication communication

Status of the Data Warehouse Status of the Data Warehouse InitiativeInitiative

Development

Operations

Campus Rollout

Data Access Policy

DW Program TimelineDW Program Timeline

Infrastructure Planning/StaffingSoftwareDatabase/HardwareProduction Platform

Policy Data PolicyDatamarts Finance/Research Req

Position Cntrl/LaborHuman ResourcesEnrollmentGrad Financial AidUndergrad Fin AidContracts & GrantsAdmissions Pipeline

Operations SupportSoftware UpgradeDatabase UpgradeHardware Growth

FY02 FY03 FY04 FY05

RolloutDev & Test

Data Warehouse Operations Data Warehouse Operations SupportSupport

Transitioning from Development to OperationsTransitioning from Development to OperationsPortal AdministrationPortal AdministrationDash Board maintenanceDash Board maintenanceData Marts maintenance Data Marts maintenance Users supportUsers supportData Base AdministrationData Base AdministrationBrio documents development, support, and Brio documents development, support, and administrationadministrationInformatica AdministrationInformatica Administration

On – Going TrainingOn – Going Training

Functional TrainingFunctional Training

Brio trainingBrio training

Refreshers courses: Finance/Research, Refreshers courses: Finance/Research, Labor, HR, Enrollment, GFA, etc.Labor, HR, Enrollment, GFA, etc.

Advance cursesAdvance curses

DW User Support levelsDW User Support levels

Signing up for sessionsSigning up for sessionsCreating user profiles/securityCreating user profiles/securityInstallsInstallsPublishing requestsPublishing requestsGeneral problems/questionsGeneral problems/questions5-10 Emails Daily5-10 Emails Daily2-4 Calls Daily2-4 Calls Daily1-2 Major problems that need extensive work 1-2 Major problems that need extensive work from developers/front-end technical support from developers/front-end technical support on a daily basis.on a daily basis.

Data Policy AdministrationData Policy Administration

Each Data Policy is administered by the Each Data Policy is administered by the appropriate Committee appointed at the VP appropriate Committee appointed at the VP levellevelRequests outside the policy are submitted in Requests outside the policy are submitted in writing to the Data Warehouse groupwriting to the Data Warehouse groupThe Committee has the discretion to either The Committee has the discretion to either authorize/deny access or recommend access authorize/deny access or recommend access to the appropriate VP depending on the nature to the appropriate VP depending on the nature of the request.of the request.The respective portfolio owner are notified of The respective portfolio owner are notified of access granted.access granted.

MaintenanceMaintenanceDW Maintenance - DM Review

  Month in Production

Role 1-3 4-6 7+

Business Staff 10% 10% 10%

Power user 60% 45% 20%

Data Warehouse Administrator 75% 50% 30%

OLAP/Reporting Tool Administrator/Developer 80% 40% 30%

Data modeler 20% 10% 5%

ETL Specialist 75% 50% 25%

Development DBA 50% 25% 10%

Operating System Administrator 20% 10% 5%

Operations 25% 25% 10%

Production DBA 20% 10% 10%

 

DM Review 2003 Resource Guide    

RPI ResourcesRPI ResourcesRole  

Business Staff  

Power user  

IT Group  

Data Warehouse Management 1

OLAP/Reporting Tool Administrator/Developer 0.5

Data modeler 0.25

ETL Specialist 3.5

DBA 0.5

Operating System Administrator 0.25

Operations (Desktop, Security set-up, etc.) 0.5

Training 1

Customer Support 0.5

   

 Total 8

Benefits GainedBenefits Gained

Empowers decision-makersEmpowers decision-makers

RedirectsRedirects costly personnel hourscostly personnel hours

Enhances institutional Enhances institutional effectivenesseffectiveness

Improves integrity and conformity Improves integrity and conformity of campus-wide informationof campus-wide information

Promotes the “no walls” culture.Promotes the “no walls” culture. Improves data quality over timeImproves data quality over time. .

Kirsten M. Volpi, Kirsten M. Volpi, Assistant VP/Controller Assistant VP/Controller

““...There has been analysis that we have not been able to get ...There has been analysis that we have not been able to get at before because the data was not retrievable in a fashion at before because the data was not retrievable in a fashion conducive to perform analytics.  For instance, we have conducive to perform analytics.  For instance, we have begun utilizing the warehouse to begun utilizing the warehouse to analyzeanalyze the indirect cost the indirect cost yield on our research grants.  This data was not readily yield on our research grants.  This data was not readily available before.”available before.”

““We are also using the warehouse not only for analytics but for We are also using the warehouse not only for analytics but for reportsreports to assist with monitoring compliance with internal to assist with monitoring compliance with internal policies, assisting with data gathering for external surveys, policies, assisting with data gathering for external surveys, as well as assisting with automating certain processes as well as assisting with automating certain processes (encumbrances for graduate financial aid).”(encumbrances for graduate financial aid).”

  

Eileen G. McLoughlin, Eileen G. McLoughlin, Director of Financial Planning & BudgetDirector of Financial Planning & Budget

““The Budget material was consolidated The Budget material was consolidated two weeks soonertwo weeks sooner than the than the previous years.  Many factors contributed to the success, however a previous years.  Many factors contributed to the success, however a significant contributor was the data warehouse allowing the Budget significant contributor was the data warehouse allowing the Budget Office to provide data and analysis of the data to decision makers Office to provide data and analysis of the data to decision makers faster than in the past.” faster than in the past.” “…“…reinforces the “no walls” culture – i.e. as the warehouse becomes reinforces the “no walls” culture – i.e. as the warehouse becomes known as the one and only data source – this will contribute towards known as the one and only data source – this will contribute towards individuals recognizing that we are one organization with individuals recognizing that we are one organization with one one version of the truthversion of the truth.“.““…“…Improved quality over timeImproved quality over time, integrity, conformity – as data is , integrity, conformity – as data is viewed and questioned issues have and will come to the surface on viewed and questioned issues have and will come to the surface on processes that impact data.  This has occurred in the budget office, processes that impact data.  This has occurred in the budget office, accounting practices have been simplified so the resultant data is accounting practices have been simplified so the resultant data is more easily interpreted”more easily interpreted”

Diane Veros, Diane Veros, Director Research AccountingDirector Research Accounting

““The Data warehouse along with the BRIO software has The Data warehouse along with the BRIO software has proven to be an extremely useful tool for providing proven to be an extremely useful tool for providing information for reporting, monitoring and analysis.  BRIO information for reporting, monitoring and analysis.  BRIO queries and pivot tables have definitely helped to make queries and pivot tables have definitely helped to make some of our work more some of our work more efficient and effectiveefficient and effective.  We have .  We have developed queries for monitoring reports, verifying data developed queries for monitoring reports, verifying data integrity, and analysis that before would have required integrity, and analysis that before would have required days, weeks, or even months working with IACS to days, weeks, or even months working with IACS to program and develop.  Once developed, those older program and develop.  Once developed, those older reports (and/or the data in them) would have allowed reports (and/or the data in them) would have allowed limited access to campus, and another user might have limited access to campus, and another user might have started from scratch to produce a similar report.  The started from scratch to produce a similar report.  The data warehouse provides a consistent data stream that data warehouse provides a consistent data stream that allows allows all campus users to view and analyze the same all campus users to view and analyze the same informationinformation in many alternative ways.” in many alternative ways.”

Jeff Tanis, Jeff Tanis, Manager of Financial Operations Manager of Financial Operations

School of ScienceSchool of Science““The time it has taken me to gather information has been The time it has taken me to gather information has been

cut by at least half. I now query the warehouse--where cut by at least half. I now query the warehouse--where previously I had to initiate many e-mails and phone calls previously I had to initiate many e-mails and phone calls to collect what I needed. Last month while doing a to collect what I needed. Last month while doing a research expenditure analysis, it took me a matter of research expenditure analysis, it took me a matter of hourshours--where in the past it took --where in the past it took daysdays to get what I to get what I needed.”needed.”

““While doing a research expenditure analysis last month I While doing a research expenditure analysis last month I identified a substantial amount of research expenditures identified a substantial amount of research expenditures on other schools grants using School of Science Orgs. I on other schools grants using School of Science Orgs. I could not have could not have identified identified and subsequently corrected and subsequently corrected these these errorserrors without the use of the Data Warehouse.” without the use of the Data Warehouse.”

Helen Grzymala, Helen Grzymala, Associate Director BudgetAssociate Director Budget

““As we roll the Finance Data Mart out to all Portfolio Financial As we roll the Finance Data Mart out to all Portfolio Financial Managers, the Budget Office will be providing more and more Managers, the Budget Office will be providing more and more reports via the Data Warehouse. Portfolios will be able to see the reports via the Data Warehouse. Portfolios will be able to see the various reports that are prepared on an various reports that are prepared on an Institutional levelInstitutional level for the for the data. We will be able to have ongoing, data. We will be able to have ongoing, meaningful discussions meaningful discussions about the dataabout the data, rather than how to get the data and how to , rather than how to get the data and how to manipulate it.”manipulate it.”

““The Data Warehouse will result in a change in job expectations for The Data Warehouse will result in a change in job expectations for both the Budget Office and the Portfolio Financial Managers. The both the Budget Office and the Portfolio Financial Managers. The forecast and budget process will evolve to a more analytical review forecast and budget process will evolve to a more analytical review of history and a fact-based projection of the future. Users will move of history and a fact-based projection of the future. Users will move from simply ‘crunching the numbers’ because they will have more from simply ‘crunching the numbers’ because they will have more time and because more data is actually available. Once the time and because more data is actually available. Once the Contracts and Grants information is available, the research units will Contracts and Grants information is available, the research units will be able to track activity right from the pre-proposal stage thru the be able to track activity right from the pre-proposal stage thru the award close out. Using this data, trending and other analysis will award close out. Using this data, trending and other analysis will follow, leading to follow, leading to more accurate forecasts and budgetsmore accurate forecasts and budgets.”.”

BenefitsBenefits

User NameUser Name Task PerformedTask Performed Pre Data Warehouse Pre Data Warehouse ImplementationImplementation

Post Data Warehouse Post Data Warehouse ImplementationImplementation

Sandra Sandra RedemannRedemannButcherButcher

Portfolio YTD Portfolio YTD AnalysisAnalysis

Half DayHalf Day to retrieve and to retrieve and compile information compile information manually.manually.

SecondsSeconds to retrieve to retrieve information from the Data information from the Data Warehouse. Warehouse.

Gina RicciGina Ricci Report AnalysisReport Analysis Multiple TruthsMultiple Truths existed existed across campus. Multiple across campus. Multiple information sources information sources existed, which destroyed existed, which destroyed data integrity and data integrity and conformity. conformity.

One TruthOne Truth exists. One exists. One information source information source promotes a common promotes a common understanding of the data understanding of the data and allows users to derive and allows users to derive at the same conclusions. at the same conclusions.

Tanya Tanya StruzinskyStruzinsky

Available Available Balance ReportBalance Report

2 Weeks2 Weeks to retrieve and to retrieve and compile information compile information manually.manually.

30 Minutes30 Minutes to build the to build the report in the Data report in the Data Warehouse, which can be Warehouse, which can be refreshed daily in Seconds.refreshed daily in Seconds.

Donna Donna TomlinsonTomlinson

Org 3 Year Org 3 Year Comparison By Comparison By Account Group Account Group

Not Readily AvailableNot Readily Available Readily AvailableReadily Available on on demand.demand.

BenefitsBenefits

User NameUser Name Task PerformedTask Performed Pre Data Warehouse Pre Data Warehouse ImplementationImplementation

Post Data Warehouse Post Data Warehouse ImplementationImplementation

Jeff TanisJeff Tanis Research Research Expenditure Expenditure AnalysisAnalysis

Multiple DaysMultiple Days to retrieve to retrieve data from multiple sources data from multiple sources and compile information and compile information manually.manually.

Few HoursFew Hours to retrieve to retrieve information from the Data information from the Data Warehouse. Warehouse.

Diane Diane VerosVeros

Data Integrity Data Integrity VerificationVerification

Days, Weeks or MonthsDays, Weeks or Months to to develop reports to ensure develop reports to ensure data integrity or to perform data integrity or to perform analysis.analysis.

Few HoursFew Hours to develop to develop reports in the Data reports in the Data Warehouse to ensure data Warehouse to ensure data integrity or to perform integrity or to perform analysis.analysis.

Tanya Tanya StruzinskyStruzinsky

Credit Card Credit Card Transaction Transaction ReconciliationReconciliation

2-3 Hours2-3 Hours to compile, to compile, review and verify credit review and verify credit card transactions for each card transactions for each user. user.

5 Minutes5 Minutes to retrieve, to retrieve, review and verify credit review and verify credit card transactions for each card transactions for each user. user.

Sandra Sandra RedemannRedemannButcherButcher

Month-End Month-End Report Report

2 Days2 Days to retrieve and to retrieve and verify program and activity verify program and activity codes in order to ensure codes in order to ensure accurate results.accurate results.

2 Hours2 Hours to retrieve to retrieve information from the Data information from the Data Warehouse. No data Warehouse. No data manipulation required.manipulation required.

Program metricsProgram metrics

Web access only (not including desktop or Dash Boards users)Web access only (not including desktop or Dash Boards users)Timeframes: January 27 – July 31Timeframes: January 27 – July 31

Financial Analysis Web Access Financial Analysis Web Access

Lessons LearnedLessons Learned

Picture worth thousand words – prototypePicture worth thousand words – prototypeFunding (time, resources, and dollars)Funding (time, resources, and dollars)Business Sponsorship – find the Champion and promote Business Sponsorship – find the Champion and promote themthemProperly designed Organizational Structure helps to Properly designed Organizational Structure helps to navigate political obstaclesnavigate political obstaclesPartnership with the Business users – build it alone and they Partnership with the Business users – build it alone and they will never comewill never comeIdentify your Business ‘Stars’ as early as possibleIdentify your Business ‘Stars’ as early as possibleJAD and RAD approaches are best fitted for the iterative JAD and RAD approaches are best fitted for the iterative DW developmentDW developmentDash Boards – unless it is visible it is not thereDash Boards – unless it is visible it is not thereBuilding Data Warehouse is far more than a technical Building Data Warehouse is far more than a technical endeavor it is all about changing the culture endeavor it is all about changing the culture

Questions ???Questions ???Ora Fish

fisho2@rpi.edu

?