fivetran/great_expectations

What it solves

It addresses the challenge of maintaining data quality and institutional knowledge within data teams. It provides a way to express and test data quality requirements using a common language, preventing data errors from flowing through pipelines.

How it works

The tool uses "Expectations," which act as expressive and extensible unit tests for data. By defining these expectations, teams can validate their data and automatically generate documentation for the validation results, ensuring all stakeholders remain aligned on data standards.

Who it’s for

Data teams who need to ensure the reliability of their data sources and maintain clear, documented quality standards.

Highlights

• Unit Tests for Data: Uses Expectations to create intuitive data quality tests.
• Automatic Documentation: Generates documentation from validation results to preserve institutional knowledge.
• Coomunity-Driven: Built on the collective wisdom of thousands of community members.