Refactor dbt models without changing consumer output
When one model is hundreds of lines long and nobody dares touch it.
- Transformation
Rebuild something already in production and prove the new form behaves like the old one.
When one model is hundreds of lines long and nobody dares touch it.
A dbt model is correct but a full refresh is too slow or too expensive to run routinely.
When a definition changed and months of history need recomputing, but a full refresh would take all weekend.
When a scheduled SQL script is the real production logic and nobody can prove a rebuild would match it.
When the nightly load is a stored procedure nobody fully understands anymore.
When the connector bill changed shape, or the connector has been broken with a pending fix for weeks.
When a materialized view refreshes on a schedule nobody wrote down and downstream reports assume that cadence.
When a transformation only exists as a notebook someone runs by hand before the numbers go out.
When a Spark notebook is the only thing that lands a source into bronze and nobody can run it unattended.
When a scalar SQL function is called from a dozen models and lives outside version control.