This page includes example notebooks that illustrate the feature engineering workflow in Databricks for both Feature Engineering in Unity Catalog and workspace feature store scenarios.
With Databricks Runtime 13.2 and above, any Delta table in Unity Catalog that has a primary key is automatically a feature table that you can use for model training and inference. When you use a table registered in Unity Catalog as a feature table, all Unity Catalog capabilities are automatically available to the feature table. Feature Engineering in Unity Catalog is in Public Preview.
The Basic Feature Store example notebook steps you through how to create a feature store table, use it to train a model, and then perform batch scoring using automatic feature lookup. It also introduces you to the Feature Store UI and shows how you can use it to search for features and understand how features are created and used.
Use the following notebook if your workspace is not enabled for Unity Catalog.