Agentic Analytics on Databricks Lakehouse
Overview
| Experience | In Person |
|---|---|
| Track | Data Warehousing |
| Industry | Enterprise Technology |
| Technologies | Databricks SQL |
| Skill Level | Advanced |
Agents promise to scale instant access to data insights across organizations. However, most data warehouses were built for humans reading dashboards. Agents expose every assumption that breaks. Flawed semantics lead to hallucination, fragmented governance exposes improper data access, and cost/performance issues explode when one analyst becomes a thousand agents. In this session we'll walk through what agentic analytics looks like in practice on Databricks Lakehouse, demoing the patterns customers are running in production today. Following these patterns, you can dramatically increase your data team's impact across your organization while reducing time-to-insight. You'll leave with a clear model of approaches to agentic analytics at scale, and see why Databricks Lakehouse is built for it.
Session Speakers
Moe Steller
/Adoption Lead, AI + DBSQL
Databricks
Ben Tripp
/Associate Product Manager
Databricks