awesome-data-quality
github.com/sujjadshaik/awesome-data-quality ↗A curated list of resources for testing, monitoring, and improving data quality across various data environments.
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Installation instructions →What's inside
Articles and Guides
Books and Methodologies
Frameworks and Libraries
- GitHubOpen Source
Another data quality monitoring tool implemented using Spark.
- GitHubOpen Source
Enables data testing through extended SQL queries.
- GitHubOpen Source
Python library for assessing data quality throughout stages of the data pipeline development.
- GitHubOpen Source
Data monitoring and observability tailored to dbt.
- GitHubCommercial
Metadata service for collecting, aggregating, and visualizing a data ecosystem's metadata.
- GitHubOpen Source
Data Quality solution for distributed data systems at any scale in both streaming and batch data context.
Tools
- GitHubOpen Source Tools
Behavior-driven development tool for data quality testing.
- GitHubOpen Source Tools
Python library for data reliability.
- GitHubOpen Source Tools
Data transformation tool with built-in testing capabilities.
- GitHubOpen Source Tools
For defining unit tests for data.
- GitHubOpen Source Tools
Automates data quality checks.
- GitHubOpen Source Tools
Data validation and profiling.
Showing a sample of 46 resources. View the full list on GitHub →