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Deequ

Deequ

Last updated , generated by Sumble
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What is Deequ?

Deequ is a library built on top of Apache Spark for defining and calculating data quality metrics. It helps in automatically verifying data by suggesting checks based on the data and allows users to define custom checks for various data quality dimensions, such as completeness, consistency, accuracy, and validity. It is commonly used for data validation in ETL pipelines and machine learning workflows to ensure data reliability and accuracy. Deequ also integrates with AWS services, making it easier to use within AWS environments.

What other technologies are related to Deequ?

Deequ Competitor Technologies

Apache Griffin is another open-source data quality solution, offering similar functionality to Deequ.
mentioned alongside Deequ in 85% (276) of relevant job posts
Great Expectations is an open source framework that helps you validate, document, and profile your data to maintain quality and improve communication between teams.
mentioned alongside Deequ in 18% (374) of relevant job posts

Deequ Complementary Technologies

Azure Synapse is a data warehouse and analytics service where Deequ can be used to ensure data quality within the data pipelines.
mentioned alongside Deequ in 0% (242) of relevant job posts
Deequ is often used with PySpark for data quality checks within Spark-based data processing pipelines.
mentioned alongside Deequ in 0% (259) of relevant job posts
AWS Redshift is a data warehouse service where Deequ can be used to validate data quality in data pipelines.
mentioned alongside Deequ in 0% (283) of relevant job posts

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