What your lakehouse needs for agentic AI

Your lakehouse was built to centralize storage, governance, and compute. But powering agentic AI takes more than infrastructure.

When analysts and business experts can’t help shape trusted, AI-ready data without engineering support, the cracks start to show. And governance becomes harder to maintain at the point where decisions are made.

In this on-demand webinar, TDWI research fellow Donald Farmer joins experts from Databricks and Alteryx to examine what modern lakehouse architecture must include to support accountable, production-ready AI.

Learn how to:

• Keep transformations and analytics inside the data platform with pushdown execution to reduce data movement and control cost
• Expand analyst contribution through governed self-service without weakening compliance or oversight
• Build semantically rich, business-ready data foundations for AI you can explain, audit, and defend
• Move from ad hoc analysis toward more automated, AI-driven decision-making without rearchitecting what already works

If agentic AI is moving from idea to execution in your organization, the architecture underneath it matters more than ever.