Working in Institutional Research has allowed me to support various folks across college campuses. Among the compliance necessities, population surveys, and ad hoc data requests – the work I enjoyed most was when I could help others achieve their aim. Sometimes, that work meant getting people in the same room at the same time to align priorities around a technology implementation. Sometimes, it meant mentoring students on data acquisition methods. And other times, it meant helping colleagues understand the capabilities of modern analytics. As a consultant, I get to see the world from a wider industry lens and determine where there are opportunities to improve education systems and the experiences of those within them.

One common theme I’ve learned, regardless of industry, is that there is a lack of data interoperability among disparate systems.

In education, that translates to something like this:

The Registrar’s office can analyze student registration and grades because they understand the student information system (SIS). Professors can analyze online student engagement with their courses because they have access to the learning management system (LMS). Assessment professionals can track annual reports and related activities because they have an assessment software system. And so on…

Independent, siloed systems usually exist to make things more focused for practitioners and those served. To that end, they provide great value. It is the lack of data interoperability that becomes a significant burden.

Accidental Architecture

In Higher Ed, Institutional Research is a place where data silos often converge. Perhaps the President’s Cabinet wants to understand the influence of online course engagement on student success. Or a reputation survey might ask about the carbon footprint of commuting students and employees. One time, I was asked to append bread preference (white/wheat/multigrain) by class and location for a campus picnic!It is excellent to piece together data elements to help people with sense-making. But still, the impact on the greater system is that of an accidental architecture.

Ad hoc data convergence is not always efficient. It isn’t easy to share or replicate, and sometimes – it costs more than the value it produces.

Better Together

Like close friends, a needle and thread, or your favorite mixed beverage – data signals are better together. Shared data models with rich semantics, cloud resources, and data science techniques are being used to:

– Optimize manufacturing,
– Improve genomics research, and
– Help job seekers with accessibility needs find careers.

In education, that translates to:

The results being that the greater academic community, acting in students’ educational interest, are able to access and analyze student needs, preferences, and risks. Practitioners would continue to optimize their operational area, and university leaders and constituents are better equipped to understand the big picture and support students holistically.

Open Education Analytics

To see how this works in action, Microsoft partnered to develop an open-source project that lowers entry barriers to the Modern Analytics ecosystem for education. is a repository that contains assets for setting up a reference implementation and architecture in Azure that will take you from raw data to a Power BI report in just a couple of hours. The implementation guide contains all the steps needed to introduce the solution.

I encourage you to try it out if you’d like to bring your data together under one (virtual) roof and see immediate results. And if you are anything like me – it will also be a great tool to help others understand and contribute to some of the capabilities of modern analytics!

Here are some questions to explore after deployment:

  • What value and insights did you find in the visualizations provided in the solution?
  • How would you explain those insights to decision makers?
  • Are there elements that you would improve?
  • If this use case doesn’t apply to your school, university, or district, what makes more sense?
  • Who on your campus would be interested in seeing this deployment?
  • What questions do you have that are still unanswered?

We would be glad to discuss these questions with you or keep reading if you prefer to learn more on your own!

Learn More

If you would like to learn more about scaling and deploying Modern Analytics in education beyond the Open Education Analytics guide, 3Cloud can help you build a foundation for analytics at scale. Please contact us directly to learn more.