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August 2022 dbt Update: v1.3 beta, Tech Partner Program, and Coalesce!

· 5 min read
Lauren Craigie

Semantic layer, Python model support, the new dbt Cloud UI and IDE… there’s a lot our product team is excited to share with you at Coalesce in a few weeks.

But how these things fit together—because of where dbt Labs is headed—is what I’m most excited to discuss.

You’ll hear more in Tristan’s keynote, but this feels like a good time to remind you that Coalesce isn’t just for answering tough questions… it’s for surfacing them. For sharing challenges we’ve felt in silos, finding the people you want to solve them with, and spending the rest of the year chipping away at them. As Tristan says in his latest blog, that’s how this industry moves forward.

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What's new

  • dbt Core v1.3 beta: Do you use Python for analytics? The first beta prerelease of dbt Core v1.3—including support for dbt models written in Python—is ready to explore! Check it out, and read more about dbt supported Python models in our docs.
  • Technology Partner Program: We just launched our new Technology Partner Program with 40+ friends in the Modern Data Stack to provide consistent support for seamless integrations joint-users can trust. Check our new dbt Cloud integrations page for what’s available today!
  • Single-tenant users: dbt Cloud v1.1.60 is now available on dbt Cloud Enterprise.

What’s better

  • dbt Cloud UI: The new dbt Cloud UI is in beta, and can be opted-into by any multi-tenant dbt Cloud customer. Cleaned-up interface, better ergonomics, fewer clicks to frequently-used screens.
  • dbt Cloud IDE: Did you catch Staging last month (our quarterly product update)? The dbt Cloud IDE has been overhauled for greater speed and performance, and is now in beta—enroll to check it out!

New resources

Things to try 🛠️

Things to read 📚

Consulting corner 🌎

I just discovered the treasure trove of excellent resources from dbt Labs consulting partners, and want to start sharing more here. Here’s a few you might have missed over the summer:

  • Reduce ETL costs: I’ve only just seen this blog from Mighty Digital, but found it to be a super practical (and concise) introductory guide to rethinking your ETL pipeline with dbt.
  • Explore data: Part two of a series on exploring data brought to you by Vivanti. This post focuses on working with JSON objects in dbt, but I also recommend the preceding post if you want to see how they spun up their stack.
  • Track historical changes: Snapshots are a pretty handy feature for tracking changes in dbt, but they’re often overlooked during initial onboarding. Montreal Analytics explains how to set them up in dev/prod environments
  • Learn dbt: Have some new faces on the data team that might need an introduction to dbt? Our friends at GoDataDriven are hosting a virtual dbt Learn Sept 12-14.

Thank you!

This month’s newsletter was brought to you by: Joel, Gloria, Azzam, Amos, and me (Lauren)