Databricks Genie answers data questions in natural language, but the quality of those answers depends on how the space behind them is set up. This track shows you how to do that setup well. You'll begin with the fundamentals: writing column descriptions, adding synonyms and instructions, connecting tables, and saving example and parameterized queries. Trusted Assets come in to lock down the metrics that matter most. You'll then work through a case study, building a space from the ground up and using monitoring and benchmarks to find weak answers and fix them. A final code-along walks you through a real analytics problem end to end, so you can see where AI speeds you up and where your own judgment still matters.
Overview
Syllabus
- Introduction to Databricks Genie
- Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.
- Case Study: Sales Analytics with Databricks Genie
- Build a Databricks Genie space end-to-end: descriptions, synonyms, instructions, table relationships, example queries, monitoring, and benchmarks.
Taught by
Gang Wang and Stan Konkin