Databricks Genie Spaces

What exactly is a Databricks Genie Space, what is it used for, and how do you set one up the right way? In this complete breakdown, Zane Goodman explains how Genie Spaces let users ask natural language questions about curated business data, while giving builders the tools to teach Genie what the data actually means. You’ll learn why simply loading a bunch of tables into a Genie Space is not enough, and why metadata is the key to accurate AI-powered analytics. Zane walks through best practices like starting small with only a few tables, adding descriptions only where they matter, defining joins, using general instructions carefully, and creating SQL expressions, example queries, and SQL functions to guide Genie’s responses. You’ll also see why benchmarking is essential for validating accuracy, how Genie compares its generated SQL to your ground truth SQL, and how proposed fixes can help you improve the space over time. Finally, Zane explains how the monitor tab helps owners review user questions, capture feedback, and keep Genie Spaces accurate and useful for end users long term. 👉 On-Demand Learning - Start With The FREE Community Plan: https://prag.works/odl-trial-yt 🔗Pragmatic Works On-Demand Learning Packages: https://pragmaticworks.com/pricing/ 🔗Pragmatic Works Boot Camps: https://pragmaticworks.com/boot-camps/ 🔗Pragmatic Works Hackathons: https://pragmaticworks.com/private-training/hackathons/ 🔗Pragmatic Works Virtual Mentoring: https://pragmaticworks.com/virtual-mentoring/ 🔗Pragmatic Works Enterprise Private Training: https://pragmaticworks.com/private-training/customized-enterprise-training/ 🔗Pragmatic Works Blog: http://blog.pragmaticworks.com/ 00:00 What is a Databricks Genie Space? 00:52 Where Genie shows up in Databricks 01:55 What Genie Spaces are used for 02:54 Why loading tables is not enough 04:18 Configure data and start small with 3 to 5 tables 05:19 Add column descriptions, format assistance, and entity matching 06:15 Instructions, join