This is a summary of the provided text in one paragraph: The article discusses using ClickHouse as an offline feature store and data transformer. It covers various aspects, including why ClickHouse is chosen, how to create a feature store, and how to generate model-ready data. The article also provides examples of creating a feature store, generating features, and merging them with the original data. Additionally, it discusses strategies for improving performance and scalability, such as using materialized views and aggregating data. Finally, it touches on the importance of selecting the right approach depending on the specific use case, whether it's building from scratch, using an existing feature store, or leveraging a combination of both.