Scaling Geospatial Analytics at S&P Global Energy: From Billions of Points to AI-Powered Map Agents

Geospatial analytics at scale traditionally required separate databases, duplicating data and fragmenting insights. Databricks Spatial SQL eliminates these silos by enabling high-performance geospatial queries directly on your lakehouse, supporting billions of data points with sub-second query times. In this talk, S&P Global Energy demonstrates a unified architecture that consolidates geospatial data ingestion, querying, and AI-driven exploration on a single platform. You'll learn how to index massive geospatial datasets using H3 hierarchical hexagonal indexing, build interactive map applications with Databricks SQL Serverless, and integrate Genie for natural language queries against spatial data. See how AI agents can explore geospatial information through conversational interfaces, and how Databricks Apps allows you to deploy custom geospatial applications powered by Spatial SQL, model serving, and governance through Unity Catalog. 🤝 Stay connected: Website: https://databricks.com Twitter: https://x.com/databricks/ LinkedIn:   / databricks   Instagram:   / databricksinc   Facebook:   / databricksinc   00:00 - Welcome and Today's Focus 01:31 - Challenge Overview and Agenda 06:53 - Interactive Demo: H3 Spatial Indexing 08:13 - Pre-created Dashboards and Data Aggregation 10:16 - Genie Natural Language Queries 13:30 - Databricks Lakehouse Architecture 15:19 - Spatial SQL Functions and Capabilities 18:04 - Spatial SQL GA Announcement 21:30 - Genie Agents and Governance with Unity Catalog 24:09 - Demo Architecture: Model Serving and LLM Integration 26:18 - Building Apps with Databricks App Stack 28:11 - Resources and Community App