Awesome Data Quality Resources

A curated list of resources for testing, monitoring, and improving data quality across various data environments.

Frameworks and Libraries

elementary - Data monitoring and observability tailored to dbt. GitHub
mobydq - Tool for data engineering teams to run & automate data quality checks on their data pipeline. GitHub
ydata-quality - Python library for assessing data quality throughout stages of the data pipeline development. GitHub
great-expectations - Tool for data testing, documentation, and profiling. GitHub
deequ - Library by Amazon for defining unit tests for data with a focus on large datasets. Based on Apache Spark. GitHub
soda - Enables data testing through extended SQL queries. GitHub
dqm - Another data quality monitoring tool implemented using Spark. GitHub
owl-sanitizer - Lightweight data validation framework based on Spark. GitHub
griffin - Data Quality solution for distributed data systems at any scale in both streaming and batch data context. GitHub

Bigeye - Continuous data quality monitoring and anomaly detection. Website
Soda - Data testing and monitoring platform. Website
Databand - Data pipeline observability and monitoring. Website
Monte Carlo - Data observability platform. Website
Sifflet - Data quality monitoring and observability. Website
Validio - Real-time data quality monitoring. Website
Lightup - Data quality checks and monitoring. Website
Lantern - Data quality and observability. Website
Metaplane - Data quality monitoring for data teams. Website
Datafold - Proactive data quality platform. Website
Acceldata - Data observability and quality management. Website
Anomalo - Automated data quality monitoring. Website
Marquez - Metadata service for collecting, aggregating, and visualizing a data ecosystem's metadata. GitHub

Complete Data Quality Methodology (CDQM) - By Carlo Batini/Monica Scannapieco. Book
Data Quality Assessment Framework - By Arkady Maydanchik. Book
CIHI Information Quality Framework - From the Canadian Institute for Health Information. Resource
Enterprise Knowledge Management - By David Loshin. Book
MIKE2.0 - Open Source initiative for Enterprise Information Management. Website
Ten Steps to Quality Data and Trusted Information - By Danette McGilvray. Book
Total Information Quality Management (TIQM) - By Larry English. Book

Deequ - For defining unit tests for data. GitHub
dbt Core - Data transformation tool with built-in testing capabilities. GitHub
MobyDQ - Automates data quality checks. GitHub
Great Expectations - Data validation and profiling. GitHub
Soda Core - Python library for data reliability. GitHub
Cucumber - Behavior-driven development tool for data quality testing. GitHub

Ataccama - Comprehensive data quality and catalog suite. Website
Informatica - Data quality and observability platform. Website
Talend - Data quality solutions with real-time monitoring. Website
IBM InfoSphere QualityStage - Data quality and governance. Website
Precisely Trillium Quality - Enterprise data quality tool. Website
Adverity - Marketing data integration with data quality management. Website
Oracle Enterprise Data Quality - Robust data profiling and cleansing. Website

A Guide to Data Quality Tools: The 4 Leading Solutions - Zendata. Article
Top Data Quality Management Tools to Choose in 2024 - Mad Devs. Article
Data Quality Management: Tools, Pillars, and Best Practices - lakeFS. Article
Best Data Quality Tools for 2024: Top 10 Choices - Adverity. Article
The 8 Best Data Quality Management Tools and Software for 2025 - Solutions Review. Article
9 Best Tools for Data Quality in 2024 - Datafold. Article
Data Quality Management Best Practices: A Short Guide - Zendata. Article