dbt and Hightouch are Putting Your Transformed Data to Work

You might already be doing some of this in-house using a complex web of scripts and API calls, but a tool like Hightouch takes out all the tedious work, freeing up your data engineering resources to focus on the infrastructure work where they add the most value.

William Tsu on Blend’s Customer Success Operations team had this to say:

We use dbt to model data from various sources in our warehouse. Specifically, dbt allows us to codify and version control all the business logic that determines our company's key metrics (eg: Annual Run Rate, Customer Counts, Feature Adoption, etc.). Hightouch is then used to pipe this data out to the relevant stakeholders. This makes sure that everyone at Blend is using the same methodology when it comes to analytics.

Putting Your Data to Work

Here's what you can do today with Hightouch's native integration with dbt Cloud:

• Schedule syncs after dbt Cloud jobs: You can now put your data into action as soon as it’s been modeled by scheduling a Sync to execute after your dbt Cloud job runs. This ensures that Hightouch always performs syncs with fresh data. All you need to do is connect your account using the dbt Cloud AP, and select the job you want a sync to run after.

• Select dbt models to sync, version-controlled through git. Hightouch’s dbt model selector allows you to pull your existing dbt models via git and send data to over 60 destinations. That way, whenever you update your dbt models, Hightouch automatically reflects those changes in your syncs.

• Get full lineage for your dbt models and downstream Hightouch syncs with dbt Exposures. Your mission-critical workflows depend on Hightouch syncs. Now you can get a birds'-eye-view of your sync dependencies on your dbt lineage graph with our support for dbt Exposures.

• Validate your model changes in GitHub. As you submit pull requests in GitHub to make changes to your dbt models, Hightouch will validate your changes to make sure that your downstream syncs don't break. dbt CI checks gives data teams peace of mind that their pipelines between dbt, Hightouch, and their operational tools stay resilient.

• Visually filter modeled data through an easy-to-use UI. This provides a clear hand-off between data and business teams. Data teams own the modeling of data (using tools like dbt) and then business teams own how that modeled data should appear in their tools. The crux? This means that business teams can now ✨ self-serve ✨ data pipelines into their own tools.

And if you'd prefer to watch this in action instead of read about it, then fret not. You're in good hands: Watch Now >>>

The Future of dbt and Hightouch

Our friends over at Hightouch are pretty committed to the idea that data teams and business teams should be able to do everything in the tools they are most comfortable with. While today you can trigger syncs after dbt Cloud jobs from within Hightouch, in the near future, they want to allow teams to create entire Hightouch syncs within dbt Cloud itself.

In fact, Hightouch just moved one step closer to this dream by enabling users to configure Syncs through creating or editing JSON objects directly (which will be doable through dbt Cloud or the dbt CLI soon).

Getting Started with dbt + Hightouch

If you’re interested in getting your Reverse ETL on with dbt and Hightouch, check out the Hightouch website and docs to get started today. And if, along the way, you need a little help or just want a place to share your excitement, don’t forget to chime in on #tools-hightouch or #operational-analytics on Slack.

It's time to set your data free. After all, how would you like to be stuck in a warehouse all day?