Define Context Once in Snowflake, Consume in Power BI

Building a governed semantic layer has long been a bottleneck in analytics, and most teams end up redefining the same metrics in every BI tool. This hands-on session shows how Snowflake Horizon Context, Snowflake's governed context layer, lets you define a single trusted set of metrics, dimensions, and relationships once and reuse it everywhere, as the foundation for both BI and AI.

Next, we put it to work with Semantic View Autopilot (SVA), an AI-powered capability that automatically turns your existing Microsoft Power BI models into governed Snowflake Semantic Views. The context you have already built becomes a single source of truth that immediately powers AI experiences across Snowflake CoWork, Cortex Analyst, and Cortex Agents. We then close the loop with the XMLA endpoint for Semantic Views, which lets Power BI and Excel query your Snowflake Semantic Views directly using native DAX and MDX. You define context once in Snowflake and consume it in Power BI, with no remodeling and no metric drift.

Finally, we look beyond a single pair of tools. If you are in this webinar, you are probably not living in a single-vendor world. You have Power BI. You have Snowflake. You likely have other tools in the mix too, and the frustrating reality is that the semantic definitions you build in one place do not automatically travel to the others. We close with the Open Semantic Interchange (OSI), the open standard built to make governed context portable across the entire ecosystem.