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5 dbt mistakes I see in every startup

5 dbt mistakes I see in every startup

Data devopsdbt Data Engineer Things
Most early-stage dbt projects suffer from unsustainable configuration patterns that eventually cripple maintainability and data reliability.
What: Author details five common dbt failures: triggering full-project CI rebuilds, ignoring model contracts, suffering from incremental schema drift, misdeclaring raw tables, and sharing schemas between development and production environments.
Why it matters: Data teams frequently neglect the software engineering rigor required to manage complex SQL transformations, leading to technical debt that slows down analytics as project scale increases.
Takeaway: Switch your CI process to only run on modified models using the '--select state:modified' flag instead of running the full project on every commit.
Deep dive
  • Avoid running full-project builds in CI to save costs and time; use dbt state selection to test only changed models.
  • Use model contracts to enforce column types and constraints, preventing downstream breakages.
  • Incremental models require specific configuration to avoid silent schema drift when upstream source data changes.
  • Raw tables should be managed as sources, not as intermediate models, to maintain data lineage clarity.
  • Isolate development schemas from production to prevent accidental data corruption or schema collisions.
Decoder
  • dbt (data build tool): An open-source command-line tool that enables data analysts and engineers to transform data in their warehouse using SQL SELECT statements.
  • Model Contract: A set of constraints defined on a dbt model that ensures data structure consistency, similar to a schema definition in a programming language.
  • Schema Drift: The process where changes in source data structures (like added or dropped columns) cause failures in downstream pipelines that expect the original format.
Original article

Early dbt projects often fail from avoidable configuration debt: full-project CI rebuilds, missing model contracts, silent incremental schema drift, misdeclared raw tables, and shared dev/prod schemas.

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