what is the added benefit here

First of all, it is completely okay to run dbt directly if you prefer to do so. That said, there are a few benefits of calling dbt from meltano. 1. Integration with

meltano run

- e.g. running ELTP (extract, load, transform, publish) all in one command:

meltano run tap-gitlab target-snowflake dbt:run dbt:test tap-snowflake target-s3

2. Ability to quickly and easily toggle between environments. For instance,

prod

,

test

,

localdev

, and

ci

can each have the same functionality without bleeding into each other. In dbt terminology, Meltano Environments map to dbt target profiles. By default, Meltano ships dbt with three targets, which map to the three default meltano environments - but you are free to remap/alter these per your own projects' needs. 3. Automatic installation of dbt plugins and automatic virtual environment isolation. This means that your dbt libraries will never suffer version conflicts with other python tools you may have installed on your machine. 4. Following from point 1 above, the ability to create Meltano jobs and schedules that tackle dbt workloads inline with other data processing steps.

yes that helped a lot thank you for your effort, i might note these down for future reference