How to Accelerate AI Impact with a Feature Store and Semantic Layer on Snowflake

Now available on-demand!

Listen to presentations and best practices from top AI technologists on how data scientists can now create, select, and store business-vetted features for machine learning and modeling re-use. Learn how to leverage the compute power of Snowflake, the flexibility of Feast, and the power of AtScale’s semantic layer to automate and accelerate time to predictive insights.

You’ll learn how a semantic layer and a feature store can address why a majority of data science projects fail and how this integration ultimately serves to ensure model prediction outputs impact your business in a meaningful way.

In this Tech Talk

You will learn about:

• How Snowflake and AtScale are working together to help data scientists create production-ready ML models from the context provided in a semantic layer;
• Major pain points within the data science workflow that prevent machine learning models from being put into production environments;
• The importance of using a feature store to streamline data science operations, and why so many data science teams are turning to Feast.

Who should watch

Data, AI & BI leaders and practitioners (e.g., Chief Data Officers, data scientists, and BI/analytics professionals)