Get Deeper Observability into dbt Pipelines

This feature ensures that you don’t make potentially breaking changes in your dbt repo.

1. Jump to the Extensions tab, click dbt models and choose your connected source.

   

2. Toggle on dbt Pull Requests checks and hit save. This gives Hightouch permission to begin checking commits in your dbt Git repo. You may be prompted to re-install the Hightouch GitHub app to allow it to create commit checks.

   

3. Now, if you make an edit to one of your dbt models used in a Hightouch sync in a branch in GitHub, you should see Hightouch commit checks running.

   

4. If a model that is powering an active downstream Hightouch sync is moved or deleted, the check will fail.

   

You now have the proactive insights needed to take the appropriate next action (either deactivate the Hightouch sync or revise the changes you’re making to your dbt model to ensure that your pipelines stay resilient).

To take full advantage of these features, try using the dbt-model type for all your Hightouch models. To make it even easier to manage your resources between dbt and Hightouch, you should consider creating a directory in your dbt project specifically for models that will be used in Hightouch syncs. This could be further organized by destination (though one model could certainly be used across multiple destinations, so this may not be how you choose to organize these models), and tags could be assigned to these files or directories to help keep documentation as useful as possible.

Given the wide array of tools in the modern data ecosystem, data teams need assurances that their multi-vendor pipelines stay resilient. That’s why we’ve prioritized building and supporting industry-leading integrations into dbt Cloud. When activating their dbt models with Hightouch, data teams can be confident that they have the visibility and guardrails they need to control how data flows through their stack.

Want to learn more? Check out our other playbooks or book a demo with our team of experts today!