What Data Vault Practitioners Need to Know About Building AI That Actually Works

PLEASE NOTE: This webinar is hosted on Microsoft Teams. Once you register, please use the link to sign up on Teams.

This meetup is bought to you by Data Community sponsors, Ignition Data / IRiS.

If you're building a Lakehouse and betting on AI, the decisions you make in your Silver layer will determine whether your AI initiatives actually work. This session goes straight to the technical depth: how your Lakehouse architecture maps to what AI systems need to reason reliably, where implementations fall short, and what a genuinely AI-ready Lakehouse looks like in practice.
What we'll cover:

• Why AI failures are almost always a data foundation problem, and how a well-structured Lakehouse solves them
• How DV2 structures map to AI requirements: entity identity, temporal history, relationship graphs, and versioned business definitions
• Where implementations go wrong: an honest look at the most common failure modes
• The full AI stack architecture and how DV2 fits within Medallion on Fabric, Snowflake, and Databricks
• What Phase 1 looks like in practice: one subject area, 4-8 weeks, AI capability from the first sprint