• Learning Path
Libraries: This path is only available in the libraries listed. To access this path, purchase a license for the corresponding library.
• Data

This learning path is actively in production. More content will be added to this page as it gets published and becomes available in the library. Planned content includes: 1. Up and Running with Great Expectations (video course) 2. Connect Great Expectations to Data Sources (video course) 3. Define and Manage Expectations with Great Expectations (video course) 4. Validate and Automate Data Quality Checks with Great Expectations (video course) 5. Design Data Quality Workflows with Great Expectations (video course) 6. Build a Data Quality Workflow Using Great Expectations (code lab)

Great Expectations (GX) is an open-source Python library for building and automating data quality checks in modern data pipelines. This learning path teaches you how to connect GX to your data, define and manage expectations, validate datasets, automate checks in workflows, and design end-to-end data quality systems. In this path, you'll gain practical, repeatable patterns that help ensure your data is reliable, trustworthy, and ready for downstream analytics and engineering use.