Tony Bai
Director of Data Analytics,
Dallas College
From Complexity to Clarity: Building AI-Ready Data Architecture with Existing Tools
Wednesday, September 30, 2026 | 4:30PM–5:30PM MT
Session Type:
Poster Session
Delivery Format:
Poster Session
Higher education institutions often operate complex, multi-vendor data environments that hinder analytics, governance, and AI adoption. Although these architectures promise flexibility, they frequently introduce cost, integration challenges, and operational overhead that slow progress toward actionable insights. This session explores how one institution simplified its data ecosystem by leveraging tools already available within its existing technology environment to build an AI-ready data platform. By consolidating data lake, warehouse, and analytics capabilities, the institution reduced complexity while improving scalability, governance, and time to insight. Participants will learn practical strategies for modernizing their data architecture without adding new tools, including how to prioritize high-value data elements, align governance with analytics goals, and take a phased approach to building AI-ready infrastructure. The session will share lessons learned from transitioning away from a fragmented vendor model and demonstrate how a simplified, integrated approach can accelerate analytics and AI outcomes.
