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Expectations

Expectations

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What is Expectations?

Great Expectations is a Python library that helps data teams ensure data quality. It essentially provides a way to define, validate, and document expectations about your data. These expectations can range from simple things like checking if a column contains only positive values to more complex checks involving relationships between different tables. It is used for testing and validating data pipelines to ensure data integrity and consistency.

What other technologies are related to Expectations?

Expectations Competitor Technologies

Deequ is a library for data quality testing, similar to Expectations.
mentioned alongside Expectations in 80% (371) of relevant job posts
Apache Griffin is another data quality framework, similar in purpose to Expectations.
mentioned alongside Expectations in 83% (268) of relevant job posts
Soda is a data quality monitoring tool that overlaps with the functionality of Expectations.
mentioned alongside Expectations in 37% (210) of relevant job posts
Monte Carlo is a data observability platform that includes data quality monitoring, competing with Expectations.
mentioned alongside Expectations in 5% (116) of relevant job posts

Expectations Complementary Technologies

DBT is a data transformation tool that can be used in conjunction with Expectations for data quality after transformation.
mentioned alongside Expectations in 1% (832) of relevant job posts
Airflow is a workflow management platform that can orchestrate data quality checks defined using Expectations.
mentioned alongside Expectations in 1% (1k) of relevant job posts
Dagster is a data orchestrator that can be used to run and manage Expectations-based data quality tests.
mentioned alongside Expectations in 3% (187) of relevant job posts

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