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Data Administration Data Warehouse Implementation 9/25/01

Data Administration Data Warehouse Implementation 9/25/01. DW Current Resources. Server - IBM RS6000 S7A with 4 engines, 4GB memory, 200GB disk space, running AIX 4.3.0.  

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Data Administration Data Warehouse Implementation 9/25/01

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  1. Data AdministrationData Warehouse Implementation9/25/01

  2. DW Current Resources • Server - IBM RS6000 S7A with 4 engines, 4GB memory, 200GB disk space, running AIX 4.3.0.   • Data – 100GB disk space used to house FRS, FES, HRS and SIS Oracle extracts. This is essentially a “data dump” of the IDMS data, and “views” still need to be created. • Staff – • DBA - Henry 80%, Song 20%, Short 10%, Chen 10% • DA - Kisil 70%, Cheesman 50%, Claunch 50%, Carter 100%

  3. DW Tasks • DBA – Extract data, design Oracle DB, load data, and production support (i.e. monitor system and DB performance, enforce security, schedule backups, etc.) • Data Administration – User interface, develop requirements document for all DW projects, evaluate data quality, create DB views, develop specialized reports, test, train users, and coordinate projects. • Both – Infrastructure design (with Systems staff), and tool evaluation (ETL, OLAP and desktop reporting) with help from the C/S group.

  4. Where are we now?

  5. Where do we want to be in three years?

  6. How do we get there? • Educate users. • Develop detailed requirements documents, including “Information Value Chains” for all goals which the DW/DM is expected to address. • Data Mart approach. • Phased implementation. • Additional resources.

  7. Educate Users • Basics – “What is a Data Warehouse?” Create a “single-source-of-truth.” “What it’s not!” (All the data, with daily updates and online access.) • Change in culture – “Let’s make better decisions based on objective analysis of data.” • Set realistic expectations - No silver bullet. It can help you make better decisions, but you still have to be responsible for implementing those decisions. • Focus on institutional goals – “What is it we need to achieve? What metrics do we need to evaluate our progress in attaining goals?” • Importance of business sponsors – Make timely business decisions and support IT requests for additional funds.

  8. Course Management (I.V.C.)

  9. Enrollment Management (I.V.C.)

  10. DW Subject Areas

  11. Course Management DM – Subject Areas • Accounts (dollars for faculty and supplies) • Assets (facilities and equipment) • Benchmark Data (what and when courses offered, degree requirements) • Courses (meeting pattern, teaching mode, requirements) • Department/College (who owns the course, degree offered and requirements) • Economic Data (salary and demand by profession) • Faculty (distribution of effort, availability to teach) • Faculty Applicants (who and how many) • Population Data (who, where and what volume) • Staff (instructional support) • Students (classification, course demand)

  12. Enrollment Management DM – Subject Areas • Accounts (dollars for services, financial aid) • Assets (facilities and equipment, housing) • Benchmark Data (enrollment patterns) • Courses (meeting pattern, teaching mode, requirements, professor) • Department/College (who owns the course, degree requirements, degrees offered) • Economic Data (general condition of economy, hot professions) • Faculty (quality, student evaluations) • Population Data (who, where and what volume) • Staff (instructional support, student service area) • Students (demographics, course demand, GPA) • Student Prospects (demographics, contacts) • Student Applicants (demographics, contacts)

  13. Project SchedulePhase I, 2001-02 Infrastructure & PlanningPhase II, 2002-03 Creation of Additional Data Marts Phase III, 2003-04 Creation of Additional Data Marts

  14. Phase I – Infrastructure and Planning (2001-2002) • IDMS Data Dump to Oracle – 100% complete. • Create Views for “Data Dump” (Ad Hoc Reporting Repository) - Target completion 3Q 01-02. • WebFOCUS Implementation – Target completion 01/01/02. • Data Mining Tools for IR staff – Purchased, and planning installation. Target installation completion 12/1/01. • Establish Enterprise Standards for Key Data– Analysis and recommendations are ongoing. • Identify and Prioritize Data Mart Development – Ongoing work with Data Stewards.

  15. Phase I – Infrastructure and Planning (2001-2002) (Continued) • Select Desktop Reporting Tools– Preliminary evaluation beginning by DA, DBA and C/S staff. Selected tool(s) will be the IT standard and supported by our staff. Target completion 1/1/02. Choices: • Crystal Reports • Infomaker • SAS • WebFOCUS • Cognos • Select ETL Tools– Preliminary comparison, and funds will be requested for 02-03. Choices: • Ascential • IBM • Informatica • Oracle • SAS

  16. Phase I – Infrastructure and Planning (2001-2002) (Continued) • Develop “basic” Data Marts and Corresponding DW Functionality – • CPE – Six years of data loaded in Oracle; SAS testing underway. Target completion 11/1/01. • GASB – Requirements phase. Target project completion 2/1/02. • Course ManagementDM – Requirements phase. Target completion 4/1/02. • Enrollment Management DM – Preliminary meetings. Data will be added incrementally, with target project completion 1/1/03.

  17. Phase II – Creation of Additional Data Marts (2002-2003) • ETL Tools – Purchase and install by 11/1/02. • Create Metadata – Will need to be created for the existing Data Marts, as well as the new. Target completion for existing DM 2/1/03. • Create Additional Data Marts – Complete Enrollment DM by 7/1/03, and start/complete two or more of the following: Department Mgt., Diversity & Equity Initiatives, Grant Management, Research Management and Resource Management (accounts, personnel, etc.). • Evaluate OLAP Tools – Choices could include Cognos and Essbase. Select tool by 1/1/03, and request funds for 03-04. • Evaluate External Data Needs - Identify external data needed for the Data Marts, locate source(s), estimate cost and request funds for 03-04. Target completion 3/1/03. • Begin Preliminary Development of EIS -Executive Information System.

  18. Phase III – Creation of Additional Data Marts (2003-2004) • OLAP Tools – Purchase and install by 11/1/03. • Create Additional Data Marts – Start/complete two or more of the following: Department Mgt., Diversity & Equity Initiatives, Grant Management, Research Management and Resource Management. • Purchase and Load External Data - Target completion 7/1/04. • Continue Development of EIS - Executive Information System.

  19. New DW Resources • Server (Existing)– $84,300Additional 4 engines and 4GB memory for Data Warehouse Server. • Servers (New) –Additional servers will need to be purchased for the Ad Hoc Reporting Repository, the Data Staging Area, the Data Mining and/or OLAP tools, and for one or more of the Data Marts. Size, type and cost will vary depending on function. Goal is for remaining servers to be Intel-based to minimize cost. Cost unknown. • Storage – Additional disk space for DW server, and for other servers using Enterprise Storage System. Exact amounts for online storage and for archiving will be identified during the project requirements phase. Cost unknown.

  20. New Resources (Cont.) • Training – $21,200 • Infrastructure – “How do you design a DW environment? • Staff Training (TDWI Seminar $7,600 for 2 FTE) • Oracle DB Training ($7,200 for 4 FTE) • Technical Training – Analysis and reporting tools. ($6,400 for 4 FTE) • Onsite visits to other universities. • Consulting on Infrastructure Design – Covansys, Gavroshe, Oracle, IBM, etc. Cost unknown. • Staff – $140,000 for 2 FTE • DBA – 1 FTE (Totally devoted to DW development.) • Reporting – 1 FTE (Totally devoted to development of the EIS and/or institutional reports from DW environment.)

  21. DW Critical Issues • Personnel Resources – Need to keep people focused on DW in light of competing projects (i.e., Sybase/Omnis Conversion, WWTE, IPP, IDMS maintenance.) • Training –IT and users. • Consulting – Assistance for infrastructure planning. This is new to us! • Culture Change – Focus on goals rather than data elements. Tell us what, not how! Value in making decision based on data. Proof of concept. • Requirements Gathering –Needs to be thorough, and heavily relies on timely user decisions. Defining who the “users” are on any given project could be political. • Budget/Funding – For additional hardware, software and people. • Business Sponsor – The Data Warehouse is not another IT project. It is an enterprise initiative!

  22. Data AdministrationQUESTIONS?

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