speed of building models, performance, cloud based

SQL Transformation is the best thing which dbt have.

I primarily value how dbt shifts data transformation into a software engineering workflow. By materializing code into tables and views automatically, it lets our team focus on the transformation logic rather than DDL boilerplate. The model selection syntax is incredibly efficient for running specific segments of our DAG without wasting warehouse resources. Macros and Jinja integration have also been game-changers for modularizing our logic and reducing code repetition. I find the YAML-based unit testing to be a robust way to ensure data integrity before it reaches our BI layer. Between the two, I prefer dbt Cloud over Core because the IDE provides immediate visibility into query results and schema changes, which speeds up our development cycle. I use it every workday. Customer support was quick and responsive when I ran into issues during the initial setup of dbt with Snowflake authentication. Implementation was also straightforward when connecting it to Snowflake, and once the connection was established, I didn’t have any ongoing issues aside from needing to reauthenticate every day.