
Its existing discovery solution had served it for years, but was showing cracks. The platform’s move to a cloud-first model introduced new costs and complexity. The system wasn’t easy to use and was challenging for administrators to get accurate information. Users reported unstable performance and frequent false positives, eroding confidence in the tool’s accuracy.
The IT governance team faced a pivotal question: how can we modernize our data discovery and classification framework without disrupting academic operations?
Searching for a Smarter Way Forward
The university set a clear goal to find a reliable and accurate alternative that could deliver actionable insights about their sensitive data. Rather than layering new tools onto a less-than-desirable foundation, the team sought a solution that could strengthen discovery across endpoints and simplify data hygiene efforts.
Their approach centered on Fasoo Data Radar (FDR), a solution purpose-built to help organizations discover, classify, and manage sensitive information with precision.
By deploying FDR agents on targeted departmental machines, the institution could automatically identify files containing sensitive or regulated data such as research records, student information, and grant-related materials. Once identified, these files could be moved, secured, or deleted as part of ongoing data hygiene and compliance initiatives.
From Discovery to Governance
Unlike the previous platform, Fasoo Data Radar’s strength lies in its ability to scan deeply and accurately across diverse data types and locations. It minimizes false positives using Augmented Intelligence, allowing IT administrators to focus on verified results rather than manual cleanup.
The university prioritized discovery and classification in this initial phase, laying the groundwork for future governance and protection strategies. With FDR’s centralized dashboard, administrators gained a real-time view of sensitive data across multiple departments. Easy-to-use reporting helps quickly identify out-of-compliance systems.
For a research-driven environment, this visibility proved transformative. Teams could now:
- Identify and locate sensitive information across distributed endpoints
- Assess data risk before it becomes a compliance issue
- Enforce hygiene policies to delete redundant or outdated files
These early governance efforts established a scalable foundation for a long-term data protection strategy.
Why Discovery Accuracy Matters
Data discovery is often seen as a checkbox for compliance, but for large universities, it is much more. With FDR, discovery became a strategic enabler.
Fasoo Data Radar’s fast and high-accuracy scanning helped the institution pinpoint exactly where sensitive files resided, whether on shared drives, faculty PCs, or research servers. The ability to reduce false positives meant teams could act with confidence rather than chasing noise.
FDR helps the university comply with regulations such as FERPA, HIPAA, and GDPR.
Turning Visibility into Control
This institution’s experience underscores a broader truth: visibility is the foundation of data governance, but accuracy is what gives it value. By replacing an unreliable and expensive solution with Fasoo Data Radar, the university took a decisive step toward proactive governance.
While today’s focus is on discovery and classification, the roadmap extends further toward automated protection, policy enforcement, and lifecycle management using Fasoo’s broader data security platform.
This represents more than just a tool replacement. It reflects a cultural shift toward smarter, data-driven governance in education, where visibility, accuracy, and accountability work in unison.
A Smarter Path to Data Governance in Education
Data discovery is not the end goal. It is the beginning of a sustainable governance framework. Fasoo Data Radar enables educational institutions to discover, classify, and manage sensitive data easily, building confidence in every decision and compliance report.
By modernizing its discovery process, this research university transformed confusion into clarity and set a new standard for responsible data stewardship in the academic world.