Skip to main content

This article was written by the Untitled team and published on Fivetran’s blog.

The introduction of the open-source tool dbt has enabled a sea change in data modeling and the construction of the modern data stack as a whole. For the first time, dbt puts software engineering principles into the hands of data analysts, analytics engineers, and data engineers allowing them to rapidly iterate and create robust data models that power data products.

So how does a small company create an avid community with over 16,000 analysts discussing new ways to use the tool in an open Slack channel? The underlying premise of dbt enables the reusability of code used to perform data modeling, allowing the dbt community to create “best-practice transforms” for the most widely adopted data sources – in other words, dbt is creating a library of standardized schemas and reusable code for all data teams to take advantage of.

Read the full article on Fivetran’s blog now!

Read the full article
Josh Hall

Author Josh Hall

More posts by Josh Hall