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.

GUNDAM is a data management system that prioritizes data using language models.

🦆 Stream-first data quality monitoring in Python! Learn more: https://arxiv.org/abs/2506.06147

🔍Your Data Quality Detector / Gain insight into your data and get it ready for use before you start working with it 💡📊🛠💎

Automated Continuous Data Quality Measurement

Health Data Metrics (HDM) a Data Quality assessment Application.

Data quality, maturity and utility labelling tool for the EHDS (HealthData@EU)

Python toolkit for evaluating and visualizing the data quality of excel spreadsheets

A library to compute data quality metrics

Metis is a framework to automatically assess the quality of tabular data across multiple dimensions.

Sumeh — Unified Data Quality Framework Sumeh is a unified data quality validation framework supporting multiple backends (PySpark, Dask, Polars, DuckDB, Pandas) with centralized rule configuration.

Final project of the course "Data and Information Quality" held by Prof. Cappiello @ Politecnico di milano

DsProfiling – Dataset Profiling

Data Quality control framework for dataframes in R

Kuzzle statistical probe plugin