Getting to Know U.

Universities already collect large amounts of data from students (e.g. application data, background, GPA), faculty and staff (e.g. demographics, employment, awards), infrastructure (e.g. square footage, physical plant, power usage), finance entities (e.g. budgets, pay), research operations (e.g. awards, expenditures, patents), and the registrar (e.g. courses, programs, degrees). Such data is however siloed and not available as needed in a usable way for envisioning the status of the university. The. issues involved in attempting to extract information from the data range from the regulatory and compliance (e.g. FERPA) to accuracy and consistency. The project will focus on building tools that progress from descriptive analytics (dashboard of historical data), to predictive analytics (predict future trends), and ultimately to prescriptive analytics (perform what-if analyses).