DRAFT - DRAFT - DRAFT - DRAFT
To realize and be consistent with the UCI IT Principle - "Data are critical institutional assets" ( http://www.oit.uci.edu/consolidation/committee/uci-it-principles.php ), campus data management and governance need to be established. While non existent today, an incremental improvement can be achieved by leveraging the consolidation to look at data more comprehensively than previously possible. Data Warehousing and Decision Support will become most effective once data management improvement is implemented and in reality will be difficult to achieve without it. Moreover, the replacement of core administrative and research systems such as the legacy financial ledger and purchasing systems with Kuali FS, Kuali Coeus Research Administration, the UCPath replacement of PPS, and the planned new Student Information System offer a unique and timely opportunity for starting a much needed campus data management program. In
Why Data Management, Enterprise Data Warehousing and Decision Support?
- Consolidate and integrate data from multiple sources, including student data, teaching/course load, grants, facilities/space, financials, purchasing, and payroll in support of campus wide decision making and related information needs such as reporting, analysis, and planning.
- To provide information that is well-organized, easy to obtain, secure, accurate, timely, consistent, integrated, and appropriately detailed so that people throughout the campus -- staff, faculty, researchers, and executive-level administrators -- will be better able to assess their needs, set priorities, understand the impact of change, and fulfill their program responsibilities more efficiently.
- Provide a source of data for the campus that represents an agreed upon "truth", using a pre-agreed upon common interpretation of the data and setting data quality standards; reducing misinterpretation or misunderstanding of data and potential errors.
- Reduce the redundant project and programming effort taking place across the UCI campus to identify, catalog, organize, scrub/clean, and document data that is of common interest; leveraging FTE resources in a more effective manner and achieving synergies between units that are otherwise fragmented across UCI in data siloes.
In order to start this process, the following road map or steps are suggested:
- Obtain buy-in from CIO and a few key campus stake holders, including the Office of Planning and Budget, and get at least 1 dedicated FTE resource.
- Identify and inventory/catalog core campus systems that produce data of common interest. Document respective data owning department(s), individuals, and data stewards. Examples: Student Enrollment Data - Registrar/ Elizabeth Bennett; Student Admissions - Deborah Decker; Employee Payroll Data - Accounting and Fiscal Services/Brenda Mathias...
- Create a process that supports orderly release and tracking of restricted data that is subject to security regulation (HIPAA, SB1386, etc).
- Research and adopt a data governance methodology. Data Flux and DAMA offer some useful methodologies to consider.
- Organize a data quality or data governance group and appropriate campus leadership structure.
- Adopt a standard format to collect information necessary to catalog data and present data governance decisions to leadership.
- Conduct an assessment of the data collection and management practices and data quality of systems that produce core common campus data.
- Enter common data attribute names, descriptions, and business rules into a campus data dictionary. Document data aliases.
- Document a data flow diagram per subject area, documenting where the data is transmitted to and how often.
- Assess what it means to implement a "zero data defect" policy for this data set. Some data sets may need to be officially certified for accuracy.
- Implement a data change management strategy and policy, per data governance methodology selected.
- Create a submission and queuing mechanisms that allows submission of decision support reports or data extracts to help campus staff in their daily business. This process must be transparent and prioritization must be handled in a way that allows people to depend on timely and accurate responses to data questions.
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