In dbt, what is the purpose of the 'seeds' feature?

The 'seeds' feature in dbt serves a specific purpose of loading CSV files into the database as tables. This capability is particularly useful for incorporating static data that enhances the analytical capabilities of your models. For instance, you might have lookup tables or small datasets stored in CSV format that you want to use in your dbt project. By utilizing the seeds feature, dbt allows you to seamlessly upload these CSV files into the database, thereby making the data accessible for transformation and analysis as part of your overall data pipeline.

This feature enables a smooth integration of external data into the dbt workflow without having to write complex scripts or handle manual database interactions. It emphasizes dbt’s functionality in managing and transforming data efficiently within the analytics environment.