Using AI & Analytics to Curate myUMBC's 1st Annual Report

Behind the scenes of the inaugural myUMBC Annual Report lies a complex web of millions of records—spanning user logins, portal page views, go-link clicks, and community engagement. Transforming this massive, multi-database dataset into a clear, compelling narrative for a non-technical audience required a unique blend of data engineering rigor, strict analytical validation, and AI assistance.

In this Analytics Community of Practice (CoP) session, Collier Jones, Campus Portal Architect, will walk us through the methodology and technical process used to crunch the numbers behind the 2025–2026 report.

What You’ll Learn

• Handling Complex Data Hierarchy & Avoid Pitfalls: Lessons learned from applying role-precedence logic across overlapping roles (Faculty, Staff, Graduate, Undergraduate) and avoiding "fanout" errors that inflate dataset counts.

• Leveraging AI for Query & Topic Analysis: How AI assisted in parsing search query behavior, evaluating search response times, and processing topic categorization.

• Data to Storytelling: Applying public-release presentation standards—framing data into neutral, scannable, and accessible visual representations without editorial bias or unverifiable claims.

Whether you manage data, run reports, or are curious about practical ways to pair AI with analytics workflows at UMBC, join us for an inside look at how our campus portal data comes to life!

Note: This will be a hybrid event with lunch provided for registered participants (20 max). As such, the seat limit only applies to in-person attendees. Also, a virtual link will be sent to all registered participants the morning of the event.