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Tools that generate human-readable documentation from data quality rules.
Distinct from Documentation Validators: Distinct from Documentation Validators: focuses on generating documentation from rules rather than validating existing documentation files.
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Great Expectations is a data quality testing framework and observability platform designed to monitor the reliability of data pipelines. It provides a structured environment for defining, documenting, and automating data quality assertions, allowing teams to validate datasets against expected structure and content before they move through downstream processes. The project distinguishes itself through a declarative domain-specific language that stores quality rules as version-controlled configuration files. It utilizes an execution engine abstraction to translate these high-level assertions in
Generates human-readable documentation from validation rules to provide transparency into expected data quality.