What are the two key parts of the Feature Store?

The two key parts of the Feature Store are indeed the Feature Registry and Feature Provider.

The Feature Registry serves as a centralized catalog where features are stored and documented. This allows for easy discovery and management of features that are available across various machine learning projects. The registry helps ensure that data scientists can easily find, understand, and reuse features, promoting consistency and reducing redundancy in feature creation across teams.

On the other hand, the Feature Provider is responsible for serving these features to different machine learning models during both training and inference. It ensures that features are accessible in a reliable and efficient manner, allowing models to utilize the necessary data for predictions.

Together, these components enhance the feature engineering process, facilitate collaboration, and enable better management and governance of features in machine learning workflows.