Step 1: Install dbt-gloss First, you need to install dbt-gloss in your dbt project. You can do this using pip:
Step 2: Create a gloss.yml file Next, you need to create a gloss.yml file in the root directory of your dbt project. This file contains the naming conventions and documentation rules that dbt-gloss will enforce. Here is an example gloss.yml file:
This file defines the following rules:
- Models must start with either dim_, fact_, or stage_.
- Tests must start with test_.
- Models must have documentation that includes the description, columns, and sources fields.
You can customize these rules to fit your specific needs.
Step 3: Run dbt-gloss Once you have created your gloss.yml file, you can run dbt-gloss to enforce the naming conventions and documentation rules. To do this, run the following command in your dbt project directory:
dbt-gloss will check all the models in your project against the rules defined in gloss.yml. If any model violates a rule, dbt-gloss will generate an error message.
Step 4: Integrate dbt-gloss into your CI/CD pipeline To ensure that the naming conventions and documentation rules are consistently enforced across all dbt projects, you should integrate dbt-gloss into your CI/CD pipeline. This can be done by running the dbt gloss command as part of your pipeline’s build and test steps.
By following these steps, you can use dbt-gloss to keep the quality of your dbt projects consistent, ensuring that your naming conventions and documentation rules are always followed.
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