data-quality-frameworks

What problem does it solve?

This Skill addresses the critical need for robust data validation and quality assurance in data pipelines, preventing data errors from propagating and ensuring trustworthy data for analysis and decision-making.

Core Features & Use Cases

• Data Validation: Implement comprehensive checks using Great Expectations for schema, data types, value ranges, and more.
• Testing Frameworks: Integrate with dbt for data modeling tests and custom SQL assertions.
• Data Contracts: Define and enforce agreements on data structure, quality, and SLAs between data producers and consumers.
• Use Case: When building a new analytics dashboard, use this Skill to automatically validate that the incoming sales data meets all defined quality standards before it's loaded into the dashboard's data source.

Quick Start

Use the data-quality-frameworks skill to validate the 'orders' table using the 'orders_suite' expectation suite.