Data Science

Great Expectations – validating, documenting, and profiling data

Great Expectations (GX) helps data teams build a shared understanding of their data through quality testing, documentation, and profiling.

Data practitioners know that testing and documentation are essential for managing complex data pipelines. GX makes it possible for data science and engineering teams to quickly deploy extensible, flexible data quality testing into their data stacks. Its human-readable documentation makes the results accessible to technical and nontechnical users.

This is free and open source software.

Key Features

  • Seamless operation.
  • GX’s Data Assistants provide curated Expectations for different domains, so you can accelerate your data discovery to rapidly deploy data quality throughout your pipelines. Auto-generated Data Docs ensure your DQ documentation will always be up-to-date.
  • Flexible, extensible vocabulary for data quality—one that’s human-readable, meaningful for technical and nontechnical user.
  • Data contracts support.
  • Readable for collaboration.

Website: docs.greatexpectations.io/docs
Support: GitHub Code Repository
Developer: GX Labs and the Great Expectations community
License: Apache License 2.0

Great Expectations in action
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GE is written in Python. Learn Python with our recommended free books and free tutorials.


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Read our verdict in the software roundup.


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