Data Quality Frameworks

概要

This skill provides production-ready patterns for establishing comprehensive data quality frameworks across the modern data stack. It enables developers to implement automated validation suites using Great Expectations, define structured dbt test patterns, and enforce formal data contracts between engineering teams. By focusing on critical data dimensions like completeness, uniqueness, and timeliness, this skill helps integrate data quality checks directly into CI/CD pipelines, preventing downstream data corruption and ensuring that analytics and machine learning models operate on high-fidelity data.

主な機能

• Great Expectations suite and checkpoint configurations
• Standardized data contract definitions for cross-team alignment
• Automated data quality monitoring with Slack notification integration
• 23,194 GitHub stars
• Validation patterns for data dimensions like accuracy and freshness
• Advanced dbt testing patterns including generic and singular tests

ユースケース

• Validating raw data ingestion pipelines before processing
• Enforcing schema and quality contracts between data producers and consumers
• Automating regression testing for data models in CI/CD environments