How can you chain models in dbt?

Chaining models in dbt is achieved by defining dependencies in SQL queries using the 'ref()' function. This function is crucial for establishing relationships between different models in your dbt project. By using 'ref()', you signal to dbt that one model depends on another, allowing it to understand the order in which to build the models and ensuring that they are executed in the correct configuration.

When you use 'ref()', dbt automatically manages the relationship and builds the models in a way that optimizes performance and reliability. This helps avoid potential issues like circular dependencies and ensures that the output of one model can be used as input for another seamlessly. The ability to create these dependencies is a key feature of dbt that helps maintain a clean and organized workflow.

The other options do not effectively facilitate chaining. Manual linking in the database lacks the automated dependency tracking that dbt provides. Creating separate documentation for each model does not influence model execution order, and running models independently does not allow for relationships to be established between them. Therefore, option B is the only method that aligns with dbt best practices for managing model dependencies and workflows.