Original Coverage & Source Attribution: campustechnology.com
Fragmented Data Is Quietly Undermining Student Success and Cybersecurity Hygiene
As the new academic year kicks off, universities are under pressure to improve student outcomes, modernize campus operations, and strengthen cybersecurity, often while operating with limited resources and staff.
To meet these demands, institutions are turning to AI-powered tools to provide more personalized student support, streamline campus operations, and help IT teams identify and respond to problems faster. However, fragmented systems and siloed data limit visibility, making it harder for universities to provide timely support.
Students, staff, and partners now expect always-on services, consistent online experiences, and secure access as a baseline, yet most institutions can’t deliver on that expectation. The missing ingredient? A connected, AI-ready data foundation.
Siloed tools, teams, budgets, and resources spread across departments and campuses generate massive amounts of data. However, not having a unified view into this data and no real-time visibility into big-picture issues creates unnecessary exposure to security threats and inadvertently reduces student support because no one can see the whole picture.
Since the cost of disconnected data is measurable in dollars, hours, security risk, and student outcomes, closing that data visibility gap should be a focus for universities.
Turning Scattered Data into 24/7 Guidance
Data fragmentation carries its steepest cost in student outcomes, particularly for first-year and at-risk students. As universities look to improve the student experience, holistic data insights provide the ability to quickly identify and predict issues that are instrumental in ensuring students can find the information they need, stay productive, and connect to the tools and services essential to their learning.
Consider student retention, for example. The goal is to identify students at risk before they disengage, before they stop attending class, stop doing coursework, and decide they’re going to fail anyway and walk away. That means correlating signals, like logins, class/session attendance, laptops connection on campus WiFi, and other signals from systems, then identifying anomalies to put supports and interventions in place before students hit that failure point.
Personalized guidance, the kind that combats summer melt and first-year attrition, depends on the institution being able to see and act on student data quickly. But this is only possible once data is unified.
When Georgia State University streamlined its operations on a unified system, for example, the IT team built a proof-of-concept AI-powered application that helps students navigate the complicated financial aid process by surfacing personalized information, financial resources, student records, deadlines, and next steps. Unified data allowed its team to innovate on the student-facing problems that matter most, enhancing student experience throughout the admissions process.
Why This Was Traditionally so Hard
Historically, when leadership wanted insight into the institution’s data or wanted to properly leverage what’s available, CIOs would have to spend significant amounts of money for data warehouses, and then duplicate the data and hire a staff to manage the whole lifecycle.
