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Rapid Insight Office Hours

Join Rapid Insight (RI) product experts and fellow RI Users to talk through platform questions and hear from your peers!

Rapid Insight A Day in the Life Series: On-Demand Materials

The Day in the Life series is a practically driven walkthrough of the software. It assumes the context of data analysis for enrollment management, and is narrated in a stream…

6 steps to build a predictive model

If you use data in any capacity at all, you’re already preparing to build a model. Learn the 6 steps to design a predictive model and see which steps you've…
Data & Analytics Blog

Stakeholder Engagement: Responding to Questions about Your Predictive Modeling

Predict offers a lot of easy pathways towards answers that are front-of-mind for users and stakeholders alike. In this Deep Dive webinar, look forward to hearing about the ways that…

4 characteristics of equitable predictive models

Predictive modeling in higher education offers exciting opportunities to improve decision-making. With thoughtful planning and implementation, modeling can help your institution foster equitable outcomes. Learn 4 characteristics of equitable predictive…
Data & Analytics Blog

Digital innovation requires digital leadership. Here are 3 principles for success

Learn three guiding principles of student-centered digital change.

3 ways to improve data literacy on campus

To use data for decision-making, campus leaders must overcome obstacles to data literacy. See tested strategies from our partner schools to build and improve data literacy.
Insight Paper

Activating the Analytics Mandate

Our research found is that higher education is missing a key ingredient: a mechanism to store and source data from disparate systems, in one central location, under a governed data…
Resource Center

Enterprise Data Management Resource Center

Explore the top priorities that institutions must accomplish to improve data management, along with corresponding EAB resources.
IT Strategy Advisory Services

Building Data Literacy

Learn how to lead data-informed conversations and avoid common barriers to data literacy which will help spearhead more effective data use on campus.