What is the purpose of the 'seeds' feature in dbt?

The 'seeds' feature in dbt serves the specific purpose of loading CSV files as tables in the database. This functionality is particularly useful for bringing external data into a dbt project, allowing analysts to work with static data that may not originate from a traditional data warehouse or ETL process. By defining seed files in the dbt project, users can easily control the schema and loading process, ensuring that the data is formatted and structured according to the project's requirements.

Seeds can be handy for small datasets or reference data, such as lookup tables or initial datasets used for testing and development. Once defined, dbt compiles these seed files into the necessary SQL statements to create tables in the database when the dbt run is executed. Thus, the seeds feature effectively streamlines the integration of CSV data into the dbt workflow, facilitating the overall data transformation and analysis processes.