Jeremiah Hansen

Make your data AI-ready with the powerful combination of dbt Projects and Snowflake Semantic Views. This session demonstrates how to leverage both SQL and Python DataFrame models in dbt for flexible data engineering that appeals to Spark developers and SQL practitioners alike. Explore semantic layers, the Open Semantic Initiative (OSI) and best practices for managing semantic view lifecycles in Snowflake. Watch Snowflake CoCo's AI coding agent accelerate dbt Project development in real time, and learn to automate deployments with Snowflake CLI. Walk away with a complete, modern approach to building AI-ready data pipelines that empower both AI models and analytics tools.

This session will show customers how to build end-to-end open pipelines in Snowflake with Snowflake Open Catalog and integration service! Join us to choose from open architecture and pipeline options, and you get to decide what we build with. During the demo, we will build an integreation pipeline to ingest data from a source of your choice into an Iceberg table in Snowflake, transform it, register the tables in Open Catalog, and query the data from both Snowflake and a third-party query engine. And here's the real kicker: The audience get to pick the direction we go. Don't miss out this fun, demo session with us.