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Analytics engineers, DQ owners ≈ 2–3 days practice

DQ with dbt

From tests and history to a cockpit — data quality as an operating discipline, not a one-off audit.

Start as sprint plan Opens the Sprint Planner with a matching template.

  1. 1. DQ language and ownership

    Fitness for purpose, steward, and contract before the first test.

  2. 2. Series: operational data quality

    KPIs, platform patterns, and remediation in one continuous series.

  3. 3. Generate dbt artifacts

    Macros, rules, and history as copy-paste starting points.

  4. 4. Move into operations

    Use sprint templates and the advisor so DQ does not stall in the pipeline.

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