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Great Expectations offers an intuitive approach to testing data that automatically generates widely-readable results—making vital collaboration between technical and nontechnical teams easier. Start building a shared perspective. Accelerate your data discovery.
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Great Expectations offers an intuitive approach to testing...
- GX CLOUD
Go from first login to first test result in minutes, with GX...
- GX OSS
And by defining Actions alongside your Expectations, you can...
- INTEGRATIONS
Great Expectations makes it easy to integrate data quality...
- DOCUMENTATION
Great Expectations documentation. Learn everything you need...
- EXPECTATIONS GALLERY
GX's Expectation Gallery: a rich, collaboration-ready...
- CASE STUDIES
Companies worldwide use GX to maintain data quality on their...
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Ready to shape the future of data? You’re in the right...
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Great Expectations is a framework for defining Expectations and running them against your data. Like assertions in traditional Python unit tests, Expectations provide a flexible, declarative language for describing expected behavior.
Great Expectations is a powerful platform that's revolutionizing data quality and collaboration. Find out why companies around the world are choosing GX.
GX OSS is a data quality platform designed by and for data engineers. It helps you surface issues quickly and clearly while also making it easier to collaborate with nontechnical stakeholders. Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data.
Great Expectations lets you express Conditional Expectations with a row_condition argument that can be passed to all Dataset Expectations. The row_condition argument should be a boolean expression string. In addition, you must provide the condition_parser argument which defines the syntax of conditions.
