To write data to a feature store table in Databricks, first, create a DataFrame with the dataset. Then, use the feature store API to create the table and write the DataFrame to it. To ensure data consistency, use the same schema for all stages of the machine learning pipeline.

Data consistency can be achieved by manually checking the data at each stage of the machine learning pipeline and making sure it matches the data in the feature store table.

Writing data to a feature store table in Databricks is not necessary as it can be done directly from the dataset without using a feature store.

To ensure data consistency, use different schemas for different stages of the machine learning pipeline and transform the data accordingly.