Welcome to a periodic roundup of dbt Slack - like the monthly newsletter, embodied in video form:
We caught up with Adam Stone (UK) and Tom Nagengast (California), who recently joined Netlify’s data team as analytics engineers, and found their jobs through dbt Slack.
We were curious to find out: how do you explain your job to your friends? How’d you find your job? And what’s the one thing you can’t live without as an analytics engineer?
Did you know how to use anchors (&,*) in YAML files to avoid repeating yourself?
If that’s news to you, I recommend checking out dbt community member Josh Devlin’s quick tutorial blog post walking through them: Repeating blocks in YAML.
With the beta launch of the Materialize adapter, streaming materialized views are now available in dbt Core, which opens up a world of real-time use cases (from data applications to operational automation).
If you’re interested in testing it out, hop on over to the #db-materialize channel in dbt Slack, or check out Materialize’s announcement post.
The dbt_artifacts package (built by Niall Woodward of tailsdotcom, with contributions from dbt community manager Claire Carroll) provides a handful of quickstart models to start understand the metadata from your dbt project runs.
Claire recently published a discourse post walking through the package in detail - highly recommend reading the full post here.
Curious how you’re visualizing this metadata in your projects?
To understand how dbt model changes impact your data, Datafold recently released an integration with dbt Cloud, that allows you to explore how underlying data values changed as part of your CI workflow.
Datafold’s founder, Gleb Mezhanskiy, is active in dbt Slack.
Meet Jillian Corkin, a longtime community member and newest entrant to the Fishtown community team!
See something in dbt Slack that you think should make it into the next roundup?
Cross-posting in the #show-and-tell channel is a great way to flag it, as is dropping a
+ (:heavy-plus-sign:) reaction on it.