great_expectations

Always know what to expect from your data.

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great-expectations

great-expectations • individual

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11,324

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Forks

1,706

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Activity Score

0/100

66 commits in 30d

Created

Sep 11, 2017

Project creation date

README Summary

Great Expectations is a Python-based open-source library that helps teams validate, document, and profile their data to maintain quality and catch issues early. It provides a flexible framework for creating data quality tests called 'expectations' that can be integrated into data pipelines and workflows. The tool generates human-readable documentation and data quality reports to ensure data reliability across different environments.

AI Dev Skills

Unmapped

Data Quality EngineeringData Pipeline ValidationStatistical Data ProfilingAutomated Data TestingData DocumentationData ObservabilityETL/ELT Pipeline Quality Assurance

Tags

Data Quality EngineeringData Pipeline ValidationStatistical Data ProfilingAutomated Data TestingData DocumentationData ObservabilityETL/ELT Pipeline Quality AssuranceServerlessSelf-hostedData-Centric AITelecommunicationsE-commerceData Profiling and DiscoveryInsuranceHealthcareFinancial ServicesGovernmentAI ObservabilityData Quality MonitoringTabularAutomated Data ValidationManufacturingResponsible AIOn-premiseRegression Testing for DataData Pipeline Quality AssuranceCloud APIData Contract EnforcementData Documentation GenerationMLOpsPython

Recent Activity

Updated 23 days ago

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189

Quality

production

Quality: high
Maturity: production

PM Skills

Scale & ReliabilityDeveloper Platform

Languages

Python100.0%

Timeline

Project created: Sep 11, 2017
Forked: Mar 22, 2026
Your last push: 23 days ago
Upstream last push: 7 days ago
Tracked since: Mar 21, 2026

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