Most enterprises are already mid-modernization: moving data from legacy platforms into modern lakehouses, organizing estates into Bronze, Silver, and Gold layers, and preparing a backlog of high-impact AI use cases.
However, the bottleneck is rarely the underlying data platform. Modernization stalls because teams cannot answer critical questions: Which data in the new estate is actually trustworthy? Who owns it? What breaks downstream when schemas or quality drift?
When data failures only surface at the consumption layer, remediation becomes expensive, modernization slows down, and AI deployment gets delayed.
The solution: enforce trust at every medallion layer
The path forward is focused. Roughly 20% of enterprise data drives 80% of business outcomes. By identifying those Critical Data Elements (CDEs), assigning clear ownership, and embedding automated Data Quality (DQ) gates at the Bronze, Silver, and Gold layers, you eliminate bad data before it reaches your models and reporting.
Join experts from Ataccama, Databricks and New York Power Authority for an interactive working session on building an end-to-end trust layer that accelerates data modernization and grounds AI agents in a reliable context.
What you’ll learn
- Why modernization stalls at the trust layer and how to start clean and stay trusted as you build your medallion architecture
- How to make CDE governance scale through inherited criticality and automated detection, instead of tagging assets one by one
- Where to place DQ gates across bronze, silver, and gold so defects are caught upstream rather than at the consumption layer
- A live demo showing Databricks Genie executing against governed, trust-scored data via the Ataccama MCP server.
Don’t let unverified data slow down your AI initiative. Reserve your spot today to learn how to operationalize trust across your entire medallion estate.
Speakers
