Feature Store is a centralized repository for storing and accessing features for machine learning models. It helps in maintaining consistency, reducing data duplication, and improving the efficiency of the machine learning pipeline.

To create a feature store table in Databricks, first, define the schema of the table using the StructType function. Then, create a DataFrame with the required data and schema. Finally, use the feature store API to create the table and write the DataFrame to it.

Feature Store is not necessary for machine learning pipelines as it only adds complexity and does not provide any significant benefits.

Creating a feature store table in Databricks is a manual process that requires writing custom code for each table.