Marisa Smith

I'm really glad to see unit testing is becoming normal in the analytics engineering workflow with the release of dbt's version of unit tests. It's something we at @TobikoData cared a lot about during our days at Netflix and Airbnb and we knew it had to be part of @SQLMesh on day 1. But we certainly understand that testing data is a relatively new concept and seen as a challenging chore. But hopefully with dbt's new addition, together we can make testing data as widespread as testing software. We've done a lot of thinking about how to make unit testing data easier and less painful. Here are some unique features that SQLMesh unit tests provides. 1. We can run your tests on DuckDB even if your project normally runs on a warehouse like Bigquery or Snowflake. This is made possible by SQLGlot. It's way faster, cheaper, and easier to setup then running tests against your actual warehouse. If your SQL cannot be automatically translated, you can of course run your tests on any warehouse you like sqlmesh.readthedocs.io/en/st… 2. No one likes to define the input data for tests, so we added a tool to create tests for you. Just write a query and the results will form your initial test which you can then tweak! sqlmesh.readthedocs.io/en/st…

True multi-repo support for dbt is here! If you've got a large dbt project that takes FOREVER to compile, and want to split it out into multiple repositories, @SQLMesh can help. Yesterday in the @TobikoData Slack channel, someone asked us if we could add multi-repo support for dbt. I found some time and it turned out to be pretty easy because we've already built this for SQLMesh native projects. I recorded a quick loom to show you what it will look like. This is what SQLMesh is all about. A community of folks trying to make data better for everyone. It may not work perfectly yet, but with your help we can improve it and make it amazing. loom.com/share/69c083428bb34…