data-quality-frameworks

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Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

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SKILL.md Content

Data Quality Frameworks

Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.

Use this skill when

  • Implementing data quality checks in pipelines
  • Setting up Great Expectations validation
  • Building comprehensive dbt test suites
  • Establishing data contracts between teams
  • Monitoring data quality metrics
  • Automating data validation in CI/CD

Do not use this skill when

  • The data sources are undefined or unavailable
  • You cannot modify validation rules or schemas
  • The task is unrelated to data quality or contracts

Instructions

  • Identify critical datasets and quality dimensions.
  • Define expectations/tests and contract rules.
  • Automate validation in CI/CD and schedule checks.
  • Set alerting, ownership, and remediation steps.
  • If detailed patterns are required, open 
    resources/implementation-playbook.md
    .

Safety

  • Avoid blocking critical pipelines without a fallback plan.
  • Handle sensitive data securely in validation outputs.

Resources

  • resources/implementation-playbook.md
    for detailed frameworks, templates, and examples.