A real dbt migration needs more than generated SQL. It needs a project scaffold with model files plus sources.yml and schema.yml so the output is usable inside a real dbt repository from the first export.
- One SQL file is not the same thing as a dbt-ready project.
- Deterministic model names and source references save cleanup time.
- sources.yml and schema.yml make generated dbt output immediately more useful.
Why raw SQL is not enough for dbt teams
dbt projects are organized systems, not loose query files. Even if the SQL is correct, engineers still need to create model paths, define sources, and add basic schema metadata before the migration can move forward.
What a practical dbt export should include
At minimum, a usable dbt scaffold should include model SQL, a dbt_project.yml, a schema.yml for model metadata, and a sources.yml that maps the raw inputs with stable names.
- models/<model_name>.sql
- models/schema.yml
- models/sources.yml
- dbt_project.yml
Why naming consistency matters
Most cleanup time in migration projects comes from inconsistent naming. If the generated SQL references one source name and the YAML defines another, the export becomes a starting point that still needs manual reconciliation.
Deterministic naming across SQL and YAML reduces that friction immediately.
How Deflows approaches dbt export
Deflows can export a dbt project scaffold so the generated output already resembles a real project structure. That means the migration output is closer to something your analytics engineering team can actually commit, review, and refine.
This applies regardless of the source: Tableau Prep, Alteryx, SSIS, and Power Query flows all go through the same prepare step before code generation, so the dbt scaffold output is consistent no matter which tool the flow originally came from.
Questions teams ask
Why do I need sources.yml during migration?
Because dbt source references should be explicit and consistent. sources.yml is the contract that tells the project which raw inputs the generated models are allowed to read.
Can generated dbt files still need review?
Yes. The goal is to shorten the path to a maintainable dbt project, not to skip review entirely. Teams should still validate naming, materialization, and warehouse-specific behavior.