hi everyone! I have two questions: 1. Is it possible to use a local DBT project as a transformation? If so, how can I do that? Which path should I provide? 2. When we have multiple data sources, what is the best practice for transformations? Each data source should have it's own DBT project? Or a single DBT project that is triggered for every data source?

is this because you dont want to have a remote git repository?

just to make it easier to develop 🙂

for your second questions, both approach should be doable! BTW have you read this tutorial? https://docs.airbyte.io/operator-guides/transformation-and-normalization/transformations-with-airbyte#refresh-models-partially

about the second question, cool!! that's awesome. I didn't saw that tutorial, but I'm going to use that approach. Thanks!

for first question, it might be helpful to create a github issue to implement that properly otherwise i haven’t tried so i am not sure if it works, but maybe as a shortcut workaround for the moment, you could leverage the fact that there is a local data folder always mounted to docker containers as described here: https://docs.airbyte.io/operator-guides/browsing-output-logs#csv-or-json-local-destinations-check-local-data-folder So if your git repo is inside that folder

/tmp/airbyte_local/git_repo

, you could maybe specify a git url pointing there (

/local/git_repo/

) to avoid passing by a remote git repo

cool thanks for the info 🙂