The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.

Always know what to expect from your data.

Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.

Compare tables within or across databases

Data Contracts engine for the modern data stack. https://www.soda.io

re_data - fix data issues before your users & CEO would discover them 😊

Scalable master data management, identity resolution, entity resolution, and deduplication using ML

ML powered analytics engine for outlier detection and root cause analysis.

Know your data better！Datavines is Next-gen Data Observability Platform, support metadata manage and data quality.

Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool

The premier open source Data Quality solution

Library for Semi-Automated Data Science

Possibly the fastest DataFrame-agnostic quality check library in town.

Open Source Data Quality Monitoring.

Frontend for the osmcha-django REST API

Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.

Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.

DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling,  new dataset hygiene review, AI generation of data quality validation tests, ongoing testing of data refreshes, & continuous anomaly monitoring

Make simple storing test results and visualisation of these in a BI dashboard

内嵌AI的数据质量控制系统