Data Warehousing: Changing Campus Culture
اسلاید 1: Data Warehousing: Changing Campus Culture Ora Fish, Data Warehouse Program ManagerRensselaer Polytechnic Institute
اسلاید 2: Rensselaer Polytechnic Institute (RPI)“We are the first degree granting technological university in the English-speaking world”Research University with programs in Architecture, Arts, Engineering, Humanities, Science, and Social Sciences Rensselaer enrolls over 7,500 undergraduates, graduate, and working professionals.Over 450 Rensselaer faculty members include National Science Foundation Presidential Faculty Fellows, members of the National Academy of Engineering, the National Academy of Sciences, and other eminent professional organizations.Founded in 1824 by Stephen Van Rensselaer
اسلاید 3: Fundamental ProblemOperational systems are not designed for information retrieval and analytical processing
اسلاید 4: History of DW at RensselaerFall 1998- Summer 2001: Looking for solutionFall 2001: Budgets are approvedFall 2001 - Jan 2002: Building infrastructureJan 2002 – today: Delivering Enterprise Wide Warehouse with the following areas:FinancePositionsHuman ResourcesStudent EnrollmentAdmissionsGraduate Financial AidUndergraduate Financial AidResearch (pre award, post award)Institute Advancement (in progress)
اسلاید 5: Data Warehouse groupPart of the Administrative Computing within the Division of Chief Information OfficeTotal of eight employeesResponsible for addressing campus reporting and analytical needshttp://www.rpi.edu/datawarehouse/
اسلاید 6: Our constituencyAdministrative leadership: President, VP of Finance, VP of Student Life, Provost, Dean for Graduate Admissions, Controller, Registrar, Dean of Enrollment, VP of Research, AVP of Budgets, etc. Academic leadership: Deans and Department Chairpersons, Research Center DirectorsCore Administration: Institutional Researcher, Director of Budgets, Director of Enrollment, Registrar, Director of Research Administration, etc.Core Administration Personal: responsible for carrying out centralized functions such as registration, admissions, payroll, etc.Campus Administrative Personal - Graduate Coordinator’s Assistant, Business managers across campus, Coaches, etc.Faculty
اسلاید 7: ViewpointRegardless of how well designed our star schemas are or how well the dimensions are conformed, to be effective in addressing campus decision support and analytical needs the Data Warehouse should be viewed as a service addressing information quality and campus culture
اسلاید 8: ViewpointThe true benefits can be achieved only when the new technology is adapted and becomes part of our business routine:Penetration takes timeBrings transformational changes to Processes and Culture
اسلاید 9: Successful Data Warehouse implementationClear set of Goals and ObjectivesSponsorship BudgetedDedicated staffStrong alliance between IT and BusinessImplemented as a ServiceProved implementation methodologyAddresses Information QualityServe as a catalyst for change
اسلاید 10: The Fundamental GoalThe fundamental goal of the Rensselaer Data Warehouse Initiative is to integrate administrative data into a consistent information resource that supports planning, forecasting, and decision-making processes at Rensselaer.
اسلاید 11: Data Warehouse ObjectivesServe as an information hub for Administration as well as the Academic SchoolsTransform Data into Information with embedded business definitionsInformative - Meta DataIntuitive for end user to perform ad-hoc queries and analysisAdequate response time - Retrieved within seconds
اسلاید 12: Business SponsorshipLack of Business SponsorshipPrototypeShop around and identify area where it ‘hurts’ Build a prototype and invite vendors to participateMarket to the business sideEngage and build awarenessFacilitate a visit to the peer institution Invite peer institution to your campusBe aware of offering temporary solutionsCostly in a long runWill have dissatisfied customers Wait for leadership to change
اسلاید 13: Lack of IT SponsorshipTypical reasons are: Lacking knowledge and/or expertise, Do not have necessary resources; Not enough demand or pressure from the topPossible steps:Secure fundingBring in outside help with knowledge transfer Build Prototype as a joint ventureEngage and Build awarenessEmphasize partnershipEngage Leadership (Business Sponsor) in setting IT priorities
اسلاید 14: BudgetBudget is the true indication of sponsorship support and priorityHardware and software for Production, Test, and Training environmentData base serversData base licensesETLFront-endPersonnelEducation and travelConsulting servicesContingency
اسلاید 15: Dedicated StaffNeed dedicated personnel to carry out the following functionsProject Manager/ChampionDBAModelerETL developersFront end developersSoftware administration and installationDesktop supportCustomer supportCampus trainingBusiness staff and Power user
اسلاید 16: Alignment between the IT and the Business in DW implementationTechnologyAlignmentBusinessCampusCultureInformation QualityArchitecture
اسلاید 17: Information QualityAccurate, Reliable, Consistent, RelevantRe-enforce common definitionsSet up processes to identify and clean erroneous dataSet up processes to gather relevant dataDefine policies on who will have access to what information
اسلاید 18: Culture From Transaction Processing Environment to Decision Support EnvironmentThe goal is to build analytical culture that values and promotes usage of information in decision making
اسلاید 19: Culture From Transaction Processing Environment to Decision Support EnvironmentPromotes fact based decisions where value is placed on decisions made through usage of information vs. supply of dataLowers the walls across organizational boundaries and promotes understanding of the business enterprise across different functional areasAnalytical culture requires different set of skills
اسلاید 20: Our ApproachThe approach to addressing campus informational needs can not be: A ProjectA ProductIt is a service
اسلاید 21: Implementing Data WarehouseBuild Technical ArchitectureEstablish Services in support of campus communityBuild Processes ensuring Data QualityWork with campus Leadership on addressing campus analytical culture
اسلاید 22: MethodologyAddresses long term solutionEnterprise wide integrated data warehouse vs. Departmental data martUse methodology with proven success i.e. learn from othersOverall long term planning with short time to delivery Has to include all aspects of DW implementationArchitecture addressing transformations, meta data, security, deliveryCampus rollout and trainingInformation QualityCommunicationSupport
اسلاید 23: Implementation MethodologyBuild DW FoundationDevelopSubject OrientedData MartsRelease Data Martto the CampusNext Data MartRelease Data MartTo the Core AdministrationData stewardsMaintenance and SupportCampus CommunicationContinuing Adaptation and Growth……Training
اسلاید 24: DataWarehouseSourceDatabaseSourceDatabaseOtherSources(e.g. files,spreadsheets)ETLDataMartData Cube Web ClientInterfacesApplicationServersOperationalData StoreDesktopInterfaces operational systems transactional systems extraction transformation modeling loading central repository subject-based data martsConformed dimensions metadata user-facing applications business intelligence decision-support OLAP querying reportingDecision SupportServersMetadata DATA SOURCES DATA ACQUISITION DATA WAREHOUSE DATA DELIVERY DATA CONSUMPTIONTechnical Architecture
اسلاید 25: Building DW Foundation - Technical Architecture InventoryERP – Banner from SCTETL – Power Center from InformaticaData Base – Oracle 9iModels – Star schemas with conformed dimensionsWeb Front end tools – Hyperion Performance Management (Brio), Dash Boards
اسلاید 26: Building DW Foundation – Data Security, Privacy and Access PolicyCan be defined as striking the “right” balance between data security/privacy and data accessValue of data is increased through widespread access and appropriate use, however, value is severely compromised by misinterpretation, misuse, or abuseKey oversight principle:Cabinet members, as individuals, are responsible for overseeing establishment of data management policies, procedures, and accountability for data governed within their portfolio(s), subject to cabinet review and CIO approvalSecurity& PrivacyAccess& Use
اسلاید 27: Building Subject Oriented Data MartsDetermining ConstituencyForming Implementation GroupConducting interviewsDefining Scope and TimelinesModelingExtracting, Transforming, and Loading DataDevelop Security systemTestingIdentify information gapsIdentify erroneous dataReinforce common definitionsEstablish processes to identify and clean erroneous dataEstablish processes to capture missing dataDevelop and approve Data Security PolicyRecord Meta Data – stored in Informatica repository and accessed with BrioAlignment between the Technology and Information Quality
اسلاید 28: Catalyst of ChangeRequires marketing and PRCommunicationsCheerleadingSupport at the Executive levelsLead by individual respected by allOffering campus training programs“Carrots and sticks”Re-examine existing processes: (month-end reporting)
اسلاید 29: Rollout
اسلاید 30: Recognizing BarriersPeople’s resistance to a new toolExpectations on information availability and usability for decision making are lowHabit of relying on Central Administration to provide information, or on their own sources (many versions of the ‘truth’)People will need to acquire new job skillsJob expectations will need to change
اسلاید 31: Developing Common VisionOne version of the truth – Warehoused Information was recognized as the only official source of dataData Experts across campus and across organizational boundariesPartnering with Human Resources – The DW training was included in Performance Evaluations and Job DescriptionsTraining is mandatory at all levels
اسلاید 32: Communication and Buy-intoExecutive briefings:Emphasized changes in analytical cultureRecognized BarriersEmphasized that top down approach is needed and ask for commitmentDemonstrated new capabilities via Dash Boards Demonstrated ad-hoc capabilities people within their organization haveCampus orientationsDemonstrated analytical capabilities Introduced training programs and the rollout strategyCommunicated Data PoliciesWed site
اسلاید 33: Data Warehouse Cascaded Rollout Strategy1. Core Administration2. Portfolio Level (Cabinet, Deans, Portfolio Managers)3. Department Level (Directors, Center Directors, Department Chairs, Department Financial Managers)4. Faculty
اسلاید 34: Data Mart Release to the Core AdministrationUtilizing Data Mart for internal operationsMore changes to the Data Mart are expectedEstablishing data cleanups queries and proceduresPreparing for Campus release:Developing campus training program: Developing and publishing Dash Boards, and Brio dynamic documentsDeveloping operational trainingInformation QualityImpacting Culture
اسلاید 35: Initial Tiered Access – Who will have access to whatData PoliciesCabinet; Deans; Department Chairs; Center DirectorsCore AdministrationPortfolio/Division levelDepartment levelTrainingHighLow
اسلاید 36: Demo
اسلاید 37: Common UsageDash BoardsSimple click away access to the most common topics for analysisPre build dynamic queries Build to address specific needs for informationAd-HocMeta Topics and published StarsAd-Hoc functionality within specific topic
اسلاید 38: Training MixBrio 101Basic navigation and mechanicsBrio 201Advanced analytics and reportsData TrainingData mart basics, BQYs, and star schemasOperational TrainingFocuses on practical applications , delivered by business ownersStudy HallsInformal, open agendaBest PracticesDemonstration of best practices, delivered by business ownersOne-on-OnesUsed to address specific reporting/analytical needs
اسلاید 39: Training Program OverviewTrack 2Track 3Track 1Brio 101Brio 101Level 1: Portfolio/Dept-Specific Pre-Built DocsLevel 1: Data Mart BasicsLevel 2: Advanced Brio DocumentsDashboard & Portal trainingOne-on-one or small group formatOperational TrainingOngoing Follow-upHighMediumLow
اسلاید 40: Training PhilosophyThe goal of the training program goes beyond teaching the mechanics:Need to sell the Brio tool and the projectNeed to educate on the benefits of the DWNeed to emphasize that Banner and the DW are complementary systems, i.e.,Need to continue and inspire!We are changing our analytical culture!
اسلاید 41: Addressing Information QualityEstablishing processes to capture erroneous and inconsistent dataETL process to identify errorsRejecting dataLoad data and clearly label errorsData Audit processesEnsuring that the loaded data reconciles back to the operational systemsData
اسلاید 42: Addressing Information QualityEstablishing Data Stewards roles and responsibilities The overall data integrity and conformity by instilling business practices and procedures to identify and correct erroneous and inconsistent data recorded in ERP systems Ensuring that Meta-data is up-to-dateOperational Training in information applicability and usageEstablishing processes to capture and maintain data necessary to support decisionsEnforcing Common Definitions by facilitating agreement across organizational boundariesData
اسلاید 43: Establishing services and supportAssessments of information needsExpansion and enhancement of Warehoused InformationExpansion and enhancement of Information Delivery solutionsProcess re-engineeringMonitoring data qualitySupport Assessment, Planning, and AnalysisOffering full spectrum of campus training programs
اسلاید 44: Establishing services and supportTransitioning from Development to OperationsFront-End (Hyperion Performance Suite) AdministrationETL (Power Center) AdministrationDesktop Support and AdministrationData Base AdministrationDash Board maintenanceBrio documents development, support, and administration Customer Support
اسلاید 45: Catalyst of ChangeProcesses and Culture
اسلاید 46: Changes in our ProcessesSome examples on utilization of the warehoused information in our operations:Assessment and PlanningEnrollment Planning Committee meeting utilizes the enrollment and the admission data in setting the enrollment targets and financial aid goals as they discuss the incoming class (how we did, quality, numbers, diversity, etc)Retention analysis – analyzing the admissions data to better understand how well the incoming class may be retained next yearAssessment of Employee retentionAssessment of Faculty renewal program
اسلاید 47: Changes in our ProcessesForecasting:Forecast current year sponsor research expenditures.Forecast graduate financial aid commitmentsUtilize past enrollment, retention, and financial aid information to forecast current and future year financial aid commitments to determine the affordability of various discount ratesMore accurately forecast research awardsUtilizing historical research ‘success rates’ in projecting cost sharing commitmentsMonitoring and compliance:Daily monitoring of budgets and expenditures from higher levels down to the specificsMonitor and review project to date budgetsMonitoring positions budgets vs. actuals and in conjunction with estimated future earnings are accurately projecting balancesMonitoring the allocation of graduate financial aidOperationsFinancial information is used in preparing and analyzing the financial statements, reconciling between the sub-ledger and general ledger, reviewing payroll allocationsCredit card reconciliation
اسلاید 48: Cultural ChangesEmpowers decision-makers: Getting accustomed to information availabilityPromotes the “no walls” culture: Performing analysis that could never been done beforeFrom ‘MY Data’ to ‘Our Information’Data Stewards role in improving data quality, integrity, and conformityFact based decision makingHow do we now redirect these costly personnel hoursEnhanced institutional effectiveness
اسلاید 49: Assessing Data WarehousePenetration and AdoptionNumber of users trained and their role in organizationNumber of distinct users connected monthlyNumber of monthly connectionRequests for changes and enhancementsSatisfaction surveysValueShifting IT resources from reporting to other value added activitiesProductivity savings on the business sideSavings realized by better more informed access to information
اسلاید 50: The Dreaded Return on InvestmentCalculating ROISavings in personnel and processingMore Effective Financial Aid packagingEffective recruitment strategiesIdentification of retention issues to targetMore fiscal responsiveness
اسلاید 51: BenefitsFosters data integrity and conformityOne version of the truthHelps to identify erroneous and inconsistent dataEstablishing ‘data cleanup’ proceduresValue shifts from data supplier to analysisTestimonials
اسلاید 52: What’s NextCultural shifts: Are we Higher Education and non for profit or Business? Performance planning processes and assessmentsCultural shifts towards developing Goals, Objectives, measuring outcomesKPI, Scorecards, Metrics
اسلاید 53: As a single source with common definitions, the Data Warehouse is a solid foundation for Scorecards and KPIKPI Scorecards Planning and AssessmentKPI, Scorecards Planning and AssessmentSimple Budgeting PlanningExceptions Alerts NotificationAdvance Analytics AssessmentVisualizationMining
اسلاید 54: Informational ResourcesThe data warehouse toolkit (Ralph Kimball)The data warehouse lifecycle toolkit (Ralph Kimball)Data warehouse design solutions (Christopher Adamson & Michael Venerable)
اسلاید 55: Informational ResourcesBecome a member of the data warehouse instituteVisit http://www.datawarehousing.com maintained by DataMirrorSubscribe to listserv from EDUCAUSE http://www.educause.edu/memdir/cg/cg.HtmlVisit other schools web sites via http://www.Georgetown.edu/users/allanr/dwconfig/
اسلاید 56: Questions ???Ora Fishfisho2@rpi.edu?
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