How can you document a model in dbt?

Using the 'description' keyword in the model's YAML file is an effective way to document a model in dbt. By declaring descriptions in the YAML file, you can provide clear, structured, and searchable metadata about your models, which is extremely useful for both current and future users and collaborators. This approach integrates seamlessly with dbt’s documentation generation, where YAML file descriptions are pulled in and displayed as part of the broader dbt documentation site, enhancing the readability and understanding of your data models.

While it is also possible to use comments in SQL statements to provide context within the code, this method is less visible when generating documentation. Comments help clarify logic and intentions directly in the code but do not contribute to the autogenerated documentation.

Creating a separate documentation file is not typical for documenting models in dbt. Instead, descriptions in the YAML file keep all documentation in an organized manner that team members can easily find and access alongside the model definitions.

Annotating the code directly, like using comments, serves to provide immediate context but lacks the formal structure and accessibility that YAML documentation offers to both the model developer and downstream users of the data. The use of YAML descriptions makes the documentation robust and maintainable within the dbt framework.