Central Washington University Board of Trustees February 9, 2018
Executive Summary – Data Warehouse Development On February 9, Nicolas A. Valcik (PhD), Executive Director of Institutional Effectiveness, and Andreas Bohman, Chief Information Officer, will describe the status of CWU’s data environment and articulate work to create a fully realized data warehouse. CWU has endeavored to complete this project for many years. When the data warehouse project began in 2011, the project plan failed to outline the role of the warehouse, the technology required to create it, or the definitions of data sets within it. The project has been re-scoped in order to understand costs, including labor, and to ensure a reliable and sustainable outcome. The project leads have identified the following objectives: 1. Provide a separate methodology for extracting transactional data for operational uses and decision-making. 2. Provide consistent data accessible for self-service analytics and that decision-makers can use for business-management practices; 3. Provide data for official governmental reports that is accurate and can be reproduced; 4. The data warehouse strategy will work in conjunction with public-facing data to provide credibility for the organization, both internal (e.g. dashboards) and external (university web pages); and 5. Create a methodology to produced edits for the functional users to correct host system (e.g. PeopleSoft) data before static files are transferred to the warehouse. The new project plan is laid out in two phases. The first phase will resolve issues in data integrity in the data warehouse and in the host enterprise system, and produce accurate state and federal reports. The second phase will evolve the data warehouse past the initial goals of the previous plan and increase the capacity of the warehouse to support self-serve analytics. Unlike previous plans, this new plan will take a systems approach to address construction of the data warehouse. It also will incorporate plans for data integrity of the enterprise system, accreditation requirements, construction of reports for compliance (state and federal), and self-serve analytics. Additionally, the system will eventually reduce personnel costs through automation. This presentation will discuss the needs for additional resources to decrease the time necessary for engineering the data environment, delivering existing commitments, achieving the five objectives, and enhancing capabilities. The greater the investment now the more quickly the project will be completed.
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