GX Core is the engine of the GX platform. It combines the collective wisdom of thousands of community members with a proven track record in data quality deployments worldwide, wrapped into a super-simple package for data teams.
Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data. Expectations foster collaboration by giving teams a common language to express data quality tests in an intuitive way. You can automatically generate documentation for each set of validation results, making it easy for everyone to stay on the same page. This not only simplifies your data quality processes, but helps preserve your organization’s institutional knowledge about its data.
Learn more about how data teams are using GX Core in our featured case studies.
Last Releases
- 1.5.2[FEATURE] Add SuiteParameterDict to all Expectation Kwargs (#11222) (thanks @Pascal06S) [BUGFIX] fix ValidationError in ExpectColumnPairValuesToHaveDifferenceOfCustomPercentage (#11209) (thanks @sariaslaso) [BUGFIX] add_batch_definition_whole_directory only loading 1 file (#11254) [BUGFIX] Remove datetime types from… Read more: 1.5.2
- 1.5.1[FEATURE] Add ColumnAggregateNonNullCount metric (#11229) [FEATURE] ExpectColumnProportionOfUniqueValuesToBeBetween (#11235) [DOCS] Revise use of the term “API” (#11196) [DOCS] fix link to removed content (#11232) [MAINTENANCE] Revert “[MAINTENANCE] Snowflake tests only run… Read more: 1.5.1
- 1.5.0[MINORBUMP] docs for Multi-source Expectations (#11165) [DOCS] revise use of the term “Cloud” in the Core docs (#11207) [DOCS] restore link checker (#11212) [MAINTENANCE] add warning filter (#11217) [MAINTENANCE] Update… Read more: 1.5.0
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Great Expectations – An Overview of The Data Validation Tool
Introduction Great Expectations is an open-source data validation tool that addresses critical needs in data quality and integrity. Developed to help data teams enforce consistency, accuracy, and reliability across data pipelines, Great Expectations provides a structured way to define, monitor, and enforce data expectations. Designed with data engineers, analysts, and data scientists in mind, it…