Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.
| Completeness | No missing values | expectcolumnvaluestonotbenull | | Uniqueness | No duplicates | expectcolumnvaluestobeunique | | Validity | Values in expected range | expectcolumnvaluestobeinset | | Accuracy | Data matches reality | Cross-reference validation | | Consistency | No contradictions | expectcolumnpairvaluesAtobegreaterthanB |
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. Source: dodatech/approved-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/dodatech/approved-skills --skill data-quality-frameworks Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw