Can I integrate this into a CI/CD pipeline?

Yes, the skill is designed to automate validation checks within deployment workflows to prevent low-quality data or schema-breaking changes from reaching production.

Can I use this for real-time data monitoring?

Yes, the patterns include checkpoint configurations and notification actions that can be integrated into your orchestration layer for real-time alerting on data quality failures.

Does it include dbt-specific tests?

Absolutely, it features patterns for generic dbt tests, singular business logic tests, and advanced validation using the dbt_utils package.

Which frameworks are supported by this skill?

This skill supports Great Expectations, dbt (Data Build Tool), SodaCL for data contracts, and general SQL-based validation patterns.

How does this help with Data Contracts?

It provides standardized YAML templates for defining schemas, quality specifications, and SLAs, facilitating clear agreements between data producers and consumers.

Data Quality Frameworks

Name: Data Quality Frameworks
Author: drgaciw

bydrgaciw

0•

데이터베이스 관리

Implements robust data validation and quality assurance using Great Expectations, dbt tests, and formal data contracts.

This skill provides production-ready patterns for maintaining high-integrity data pipelines by integrating industry-standard frameworks like Great Expectations and dbt. It enables developers to establish comprehensive data quality dimensions—such as completeness, uniqueness, and timeliness—while automating validation within CI/CD workflows. By implementing the data testing pyramid and formal data contracts, this skill ensures reliable data flow between producers and consumers, significantly reducing silent failures and maintaining trust in analytical and machine learning environments.

주요 기능

010 GitHub stars

02Multi-dimensional quality checks covering completeness, validity, and statistical drift

03Comprehensive dbt test suites including generic, singular, and custom validation patterns

04Implementation of formal Data Contracts for producer-consumer alignment

05Automated Great Expectations suite generation and checkpoint orchestration

06Integrated notification patterns for real-time data quality failure alerts via Slack

사용 사례

01Implementing a structured testing pyramid for data to catch schema errors and business logic issues early

02Building automated validation pipelines for cloud data warehouses like Snowflake or BigQuery

03Establishing formal data contracts to prevent breaking changes in upstream data sources

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add drgaciw/academic-compliance-hub-glm data-quality-frameworks

For use in Claude.ai and ChatGPT

Download Skill