Always know what to expect from your data.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.

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 quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io

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

Scalable identity resolution, entity resolution, data mastering and deduplication using ML

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

The premier open source Data Quality solution

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

Library for Semi-Automated Data Science

Open Source Data Quality Monitoring.

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

Frontend for the osmcha-django REST API

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

Amora Data Build Tool enables analysts and engineers to transform data on the data warehouse (BigQuery) by writing Amora Models that describe the data schema using Python's "PEP484 - Type Hints" and select statements with SQLAlchemy. Amora is able to transform Python code into SQL data transformation jobs that run inside the warehouse.

数据质量控制系统

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

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.