data-quality-checks

OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.

⚡ 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 😊

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

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Databricks framework to validate Data Quality of pySpark DataFrames

🐳 Tool to automate data quality checks on data pipelines

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

数据治理、数据质量检核/监控平台（Django+jQuery+MySQL）

Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.

An RDF Unit Testing Suite

NBi is a testing framework (add-on to NUnit) for Business Intelligence and Data Access. The main goal of this framework is to let users create tests with a declarative approach based on an Xml syntax. By the means of NBi, you don't need to develop C# or Java code to specify your tests! Either, you don't need Visual Studio or Eclipse to compile your test suite. Just create an Xml file and let the framework interpret it and play your tests. The framework is designed as an add-on of NUnit but with the possibility to port it easily to other testing frameworks.

Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.

Code for blog at https://www.startdataengineering.com/post/python-for-de/

A Stata template for running high frequency checks of incoming research data at Innovations for Poverty Action

Swiple enables you to easily observe, understand, validate and improve the quality of your data

Lightweight library to write, orchestrate and test your SQL ETL. Writing ETL with data integrity in mind.

Data Quality Monitor (DQM) - Continuously validate your data with easy, customizable rules.

hooqu is a library built on top of Pandas-like Dataframes for defining "unit tests for data". This is a spiritual port of Apache Deequ to Python

The PEDSnet Data Quality Assessment Toolkit (OMOP CDM)