Challenges, changes, and the road ahead: The state of data in higher education

Key points:

• Managing and acting on data is essential for institutional success
• Dark data: A potential source of illumination
• How higher ed can get the most out of advanced analytics
• For more news on data, visit eCN’s IT Leadership hub

Higher education has a data problem.

It’s not new: Institutions have been grappling with fragmented data for a long time. Especially when it comes to student information, sprawl is the norm. Data is housed across departments and platforms, making it nearly impossible to compile a holistic view of the institution and its student body. This means that basic questions around core metrics–things like institutional performance and student outcomes–are hard to answer.

Cleaning up and effectively managing that data has, for many institutions, become a Herculean task–one they’re often willing to ignore. Unfortunately, ignoring the problem isn’t going to make it go away. In fact, as enrollment becomes more competitive across the industry, and institutional resources become more constrained, the ability to effectively manage (and act on) data is no longer in the “nice to have” category; it’s essential.

So, how did we get here?

For decades, colleges and universities have relied on a variety of disconnected systems to manage student data: student information systems, financial aid platforms, learning management systems, and more. Each system serves its own distinct purpose, and a lack of integration among them often leads to duplicated efforts, inconsistent reporting, and missed opportunities. Locked away in functional silos accessible only to specific departments, it becomes very difficult to use that data for campus-wide initiatives.

To address this, many institutions turned to data warehouses and, more recently, data lakes. Each offers value: Data warehouses organize structured data while data lakes store large volumes of raw, unstructured content. But when implemented in isolation and without an overarching strategy to connect and contextualize the data, these tools can actually exacerbate the existing disconnect.

Without a connected strategy to contextualize and unify their data, institutions risk missing critical insights that would otherwise improve all sorts of programs, ranging from student success initiatives to enrollment planning. In this competitive environment, those are the types of insights that can be the difference between thriving and falling behind.

Recently, a more holistic model has emerged: the data lakehouse, which combines the scalability and flexibility of a data lake with the structured querying and governance features that make data warehouses so valuable. The cost benefits are clear: Instead of maintaining separate storage systems for different data types, institutions can reduce infrastructure expenses while improving data accessibility. More importantly, data lakehouses can reduce the complexity of working across multiple systems. Departments can finally work from the same dataset, eliminating the inconsistencies that plague cross-departmental initiatives. It enables a more unified, strategic use of data.

With a unified data approach like the lakehouse, institutions aren’t just simplifying their infrastructure–they’re laying the foundation for smarter, faster operations across campus. When departments can access and act on shared, reliable data, the impact is tangible.

Effective data use can also turbocharge collaboration efforts. When stakeholders from different departments are working with the same information, it becomes a lot easier to align efforts. Think of some student success initiatives that cut across functional lines, such as improving retention among first-generation students or streamlining the transfer credit evaluation process. Data transparency is crucial to launching those types of initiatives and making them succeed.

Beyond student success programs, there are tangible financial and operational advantages that stem from effective data management. Maintaining multiple data systems isn’t cheap. Consolidating data management into a single environment reduces redundancy (both in terms of licensing and IT labor), lowers long-term TCO, and has the bonus of simplifying compliance efforts and allowing institutions to scale their data strategy without the burden of starting over every time a new need emerges.

Toward a more data-driven future

The current environment is challenging and changing fast. Colleges and universities have to adapt to all sorts of seismic shifts, ranging from changing student demographics to rising student expectations to having to navigate a challenging political climate. The demand for agile, data-driven decision-making has never been greater. When used effectively, data can serve as a connective tissue linking goals with outcomes.

But a modern approach to data management must go far beyond simply storing information. Institutions must be able to use the information strategically to support student retention, fine-tune recruitment, optimize institutional operations, and ultimately fulfill the institution’s mission. Getting there isn’t easy; it involves moving beyond outdated systems and fragmented workflows.

By investing in unified, flexible data infrastructure and fostering a culture of collaboration around data, institutions can transform the way they operate and the way they serve students. In a landscape defined by rapid change, effective data strategies provide the clarity and agility needed to thrive.

About the Author:

Sam Burgio is President and Chief Operating Officer at Jenzabar.