I’ll be presenting a hands-on workshop for a live audience soon where participants will build out a data pipeline with dbt Cloud and Starburst Galaxy. As per my usual process, I record presentations & labs to see if all flows well, to catch errors, and to validate my timing estimates.
Usually, these are not shared, but I wanted to get some more eyeballs on the lab exercises (and hopefully hands on keyboards) as some feedback would be awesome. That said, no worries if you just want to watch me do the hands-on components (i.e. all but the first 10 mins of intro material).
For those who can’t wait any longer, here’s the YouTube playlist!
I need to call out that this is NOT a workshop I created from scratch. Far from it!
The original Quickstart for dbt Cloud and Starburst Galaxy was was created by Amy Chen (dbt) and then Kyle Payne (Starburst) released it as Build a data transformation pipeline with dbt and Starburst Galaxy. He enhanced it to showcase Trino/Starburst abilities of connecting to multiple data sources instead of being limited to a single source by the dbt project itself.
My spin on the workshop was to explore more features of Starburst Galaxy. These include global search, schema discovery, data quality checks, tagging, and of course, data products. I also was able to adjust some of the screenshots as some of the flows look different in both of the tools since these last ones were created.
Interested? Want to try out the labs yourself? I’d suggest watching the first video in the YouTube playlist to get your bearings and then jump into the lab guide itself as it will walk you through all of the steps for this workshop.
And absolutely feel free to provide feedback here in this blog post’s comments section or the same place on the most appropriate YouTube video in the playlist.
Here are the videos themselves!