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Fulfilling the Promise of Predictive and Prescriptive Analytics in Higher Education

It is undeniable that big data analytics provide a real opportunity to academic institutions, specifically in predictive and prescriptive analytics. However, the McKinsey Study on Higher Education shows that academic institutions have the lowest adoption of predictive and prescriptive methodology. This divide can be overcome through thoughtful analysis of an institutions' technology ecosystem and a use case driven approach to implementation. Machine Learning (ML) and Artificial Intelligence (AI) provide institutions the ability to analyze large sets of data that can be used to focus more intently on the individual learner. On a broader scale, student data can also be parsed through predictive churn to focus on finding, retaining and supporting the next generation of student freshmen.

Join AWS and ibi for a webinar as we discuss the promise of adopting predictive and prescriptive analytics and how higher education institutions are doing this successfully today.

You will learn how to apply predictive and prescriptive analytics to:

  • Targeted Student Advising
  • Adaptive Learning
  • Manage Enrollment
  • Overcoming perceived limitations


  • Deepinder Uppal, Vice President for Innovation and Technology, Public Sector, Information Builders
  • Dilip Kikla, Senior Global Redshift Business Development Specialist, AWS

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