Great AI starts with great data
Discover why data architecture—from warehousing and lakehouse design to streaming and APIs—determines whether enterprise AI scales or remains stuck in experimentation
Overview
Enterprise artificial intelligence (AI) rarely fails from lack of ambition. It fails because data is fragmented across systems that were never built to work together. In this third video of a four-part series, Holger Mueller from Constellation Research shares a clear, non-technical breakdown of what makes AI scalable: Robust warehousing, lakehouse architectures, real-time data flow, and an integration approach that preserves coherence over time.
In this video, you’ll hear:
- How the “building blocks” fit together for successful AI programs
- Why a centralized operating environment can reduce fragmentation and re‑engineering
- Why industry-shaped data models can accelerate practical AI adoption
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You have the platform. You have the data. In the final video, Holger Mueller looks at where agentic AI is gaining real traction and what enterprise leaders should prioritize now. Watch Part 4: The Next Chapter of Enterprise AI.