11AM PT, 2PM ET
The ability to make data-driven decisions and act on key insights is critical in higher education. Increasing student retention and graduation rates, improving operations and containing costs all depend on enterprise-level views of data and the use of analytics.
But oftentimes, university data is siloed across departments and requires manual and time-consuming extraction before it can be valuable.
Maryville University in St. Louis experienced this painful reality when leaders looked to use predictive analytics to identify students that were on track to drop out during their first semester and provide “just in time” intervention to increase graduation rates.
Join the Center for Digital Education on March 31 at 11 a.m. Pacific/2 p.m. Eastern as we talk with leaders from Maryville University. They will discuss how they worked with Amazon Web Services (AWS) to launch a rich data lake solution combining data from their learning management and student information systems.
Register now to hear how the university is:
- Using machine learning and artificial intelligence to improve student academic success by enabling early identification of students at risk of dropping out
- Leveraging a data lake to pool multiple sources of student data to identify students who are struggling
- Upskilling IT Staff in the practical use of more sophisticated data and analytics tools