Higher Education Data Analytics
Scaling and Accelerating Institution-Wide Analytics
George Mason University
George Mason University (GMU), founded in 1949, is a public research university that is the largest institution in the Commonwealth of Virginia. GMU has been growing steadily and does not plan on stopping anytime soon, with a 10-year goal to produce 100,000 graduates by 2024.
To help them understand how to effectively scale their enrollment yield, graduation rates, facilities, and the other factors necessary to meet this goal, they knew they needed to move beyond their existing, siloed data.
How GMU Uses the Data
Balancing Growth with Diversity and Student Success
GMU has a complex demographic of the student body. Adding international presence results in a need to create a data environment that accounts for this diversity. To grow while continuing to meet the needs of diverse learners and support student success, GMU had to reengineer their existing data infrastructure to see the bigger picture.
Institutional Challenges to Using Data Effectively
The institutional compartmentalization was one of the biggest challenges for the institution. GMU had siloed data to where they were unable to make a cohesive data infrastructure, rather, it was a mentality of ‘my data’ instead of ‘the university’s data’.
An Accelerant to Growth
As the institution was growing steadily, GMU had to build a data environment that supported their diverse and increasing student body. Establishing a data infrastructure to leverage and understand the connections among enrollment, student success, and financial data was the key to moving beyond their existing, siloed data. HelioCampus partnered with GMU to offer their expertise in data science and expand their thinking using customizable data models accessible to faculty and staff.