8 dbt Myths That Need To Be Busted
On the 7th of January 2021, I started my newsletter about data for one reason: Because of an open-source tool called dbt.
I got introduced to dbt early, together with an introduction to the fishtownanalytics mentality around ELT. I was blown away by their visionary approach and the ease of use of dbt.
But because I should’ve heard earlier about dbt and their approach, I started my newsletter to stay on top of the data world for good.
Today, 3 years later, dbt has made a lot of progress, fishtownanalytics rebranded as DbtLabs, launched a commercial cloud offering and tons of features for the open core dbt.
Dbt has become a major engine, and the competitors have grown up. Dbt changed a lot from the easy-to-use open source project I learned about at the end of 2020.
As a result of this fast development from a small open source project to a large commercial product, many myths still surround dbt.
I’m here to discuss the 8 myths I find most often, not to get you away from the tool, but to help you make the most of it!
