Understanding the Databricks Genie Landscape

Databricks Genie is now a family of products, not a single feature. Genie One, Genie Agents, Genie Ontology and Genie Code each solve a different problem and sit in a different part of the stack. In this webinar, Polestar Analytics and Databricks walk the Genie landscape end to end and show how the pieces fit together on Databricks.

The session is built around one idea: going from a raw table to an answer you can trust. Through a live demo on Azure Databricks using a retail data model, it shows how teams build with Genie Code, ask with Genie Agents, get answers in one place with Genie One, and rely on Genie Ontology and Unity Catalog to keep every answer grounded in governed data.

• Understand how the Genie family fits together: Genie Code for builders, Genie Agents for curated business domains, Genie One as the front door for business users, and Genie Ontology as the business map underneath them all.
• See Genie Code build a documented gold layer from a single plain-English prompt, test it, fix its own errors and follow your team’s naming and documentation conventions.
• Learn how Genie Agents answer direct questions in chat mode and open-ended “why” questions in agent mode, with every answer backed by SQL you can inspect, and how benchmarks validate an agent before it reaches business users.
• Discover how governance and Unity Catalog carry over automatically, so row-level permissions apply and Genie never gets more access than the person asking.
• Explore how Genie Ontology learns from metric views, domains, dashboards and frequent queries, and how OntoRank picks the most trusted definition when two assets disagree.
• Find out what it takes to prepare your data estate, from table descriptions and keys to certified metric views, so Genie returns accurate, trustworthy answers.

• Solution architects designing data and AI platforms on Databricks.
• Data engineers building pipelines that feed Databricks Genieand its ontology.
• ML engineers working with agents, context and governed data.
• Platform leads responsible for governance, access and scale.
• Teams evaluating where the Databricks Genie products fit their architecture.