1. Data-Driven University Assembly Required: the Role of the Business Intelligence Tool at VT CSG PRESENTATION MAY 14, 2015 Debbie Fulton, AVP for Enterprise Systems Virginia Tech

2. It’s not how you get there…unless you can’t get there. Delta, United, or USAir… Hertz, Enterprise, or Avis… Doesn’t really matter which you choose unless it means missing the event! The “perfect” BI tool is not the goal and will not create a data-driven university. But if you have no viable tool, your actual BI goals may be unattainable.

3. Just to be clear…. Implementing the “perfect” Business Intelligence tool does NOT create a data-driven university. Many BI tools exist that provide acceptable functionality BUT Some level of BI tool functionality is needed to advance toward a data-driven university. BI Tool Data-DrivenUniversity

4. Finding a BI Tool – Virginia Tech’s Journey Any tool will do - almost VT’s legacy reporting environment RFP for a BI tool Leveraging the tool to become a data-driven university – EAB recommendations

5. Goals for the Virginia Tech BI Tool Initiative Replace soon-to-be obsolete technology Leverage VT’s data warehouse Position VT for the future Unstructured data Mobile access Diversity of data sources Address issues with the current environment Inconsistent distribution and management of information Report development cycle is lengthy and process varies Lack of modern presentation and analytical functionality Inadequate licensing of legacy tools; product obsolescence

6. RFP Requirements for VT Business Intelligence System Pixel Perfect Enterprise Reporting Ad hoc Reporting Analytics, Visualization, and Predictive Modeling Scheduling and Distribution Dashboards Mobile implementation Common Data Model (virtual data model)

7. Virginia Tech’s Legacy Data Architecture – no common data model

8. Virginia Tech’s Data Architecture Vision for the Future: A Common Data Model

9. BI at VT: Benefits Realized and Next Steps Microstrategy site license for administrative and academic usage Have a tool with full functionality to support BI Opportunity to jumpstart BI dialogue BI sponsorship and steering committee Data Governance – beyond data stewards BI leadership and evangelism

10. Questions for consideration in achieving a data-driven university….. How do we progress with all aspects of a BI implementation (data governance, evangelism, analytics, etc.) that need to come together to reach a “data-driven” university? Where does IT fit? Could we learn from the evolution of Learning Systems for how we might create data analytics services, partnerships, and direction between IT and the university?