Stress Less, Scale More: Building a Semantic Architecture to Enable AI-Ready Data (and their humans)

Data teams are hearing the call: leadership demands AI-ready data. But while the vision is clear, the lack of concrete documentation on how to get there makes it a daunting task. How do you start the work from where you are, build a scalable semantic architecture, and prepare not just your data—but your people—to thrive in an AI-driven future?

In this session, Ritu Arora, Associate Director of Data Governance, Master Data & Reference Data Management at Bristol Myers Squibb, and Laurie Nelsen former Sr. Ontologist at Mayo Clinic and current Semantic Solutions Engineer at TopQuadrant, cover learnings from the BMS’s journey, including: semantically enriching data discovery, connecting data sources cross domain and cross systems, activating meta data, and delivering data products leveraging TopQuadrant’s flagship TopBraid EDG solution.

What You’ll Take Away:

• How to engage your team to begin AI-readiness work today, regardless of current maturity.
• Key steps to build a flexible semantic architecture that supports scaling AI initiatives.
• Practical lessons on metadata management, data discovery, and governance from industry experts.

You will leave with an understanding of how to inspire teams to start AI-ready work from wherever they are, and the next steps needed to build a scalable solution—even when the future state is still unknown.