dbt tags: Categorize and Manage Resources

In dbt, tags are a flexible way to categorize and manage different resources within your project, such as models, snapshots, and seeds. You can assign tags to these resources to facilitate selective execution of commands, making it easier to manage parts of your project during development and deployment.

Applying Tags

You can define tags in the dbt_project.yml file under the appropriate resource type. Tags can be a single string or a list of strings, depending on how many categories you want to apply to a resource.

Additionally, you can apply tags directly to individual models using the config block within the SQL file:

Using Tags for Selective Execution

Once tags are applied, you can use them to run specific parts of your project. For example, to execute all models with the weekly tag while excluding those tagged nightly:

Tags in Seeds

Tags can also be applied to seeds to group and manage static data that supports your transformations:

Hierarchical Accumulation of Tags

Tags accumulate across the hierarchy of your project configuration. For instance, if a parent node in your dbt_project.yml is tagged "sensitive_data”, all child nodes inherit this tag unless specifically overridden or extended:

Accumulation Example:

• stg_orders.sql inherits tags: ["revenue”, "critical”, "nightly”]
• dim_customers.sql in marts inherits tags: ["customer_data”, "nightly”, "sensitive_data”]

Beyond models and seeds

Tags are not limited to models and seeds; they can also be applied to sources, exposures, and even specific columns within a table. This extended functionality allows for granular control over test execution and documentation exposure.

In this setup, a unique test tagged "test_level” can be executed using the tag selector, providing a powerful way to manage tests across different layers of your data architecture.

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