In this video, I walk through a practical use case demonstrating how Semantic Views & Cortex Code in Snowflake can be used to define relationships across multiple fact and dimension tables — simplifying complex data models and making them more intelligent.
Going through it would give insights about:
1. How semantic views in Snowflake implicitly understand the context of the objects ad columns and define the relationships.
2. Step-by-step setup of a Semantic View directly within the Snowflake console.
3. The natural language question that we can ask the Agents and it can give response which is context aware.
4. How Snowflake Cortex (Cortex Code) helps modelers define relationships faster — significantly improving productivity.
This walkthrough is designed for data engineers, analytics engineers, architects, and anyone looking to enhance their data modeling approach with AI-driven intelligence.
