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Data quality as code: contracts, expectations, and stopping bad data at the door
A data pipeline can run successfully, pass every scheduled job, update every dashboard, and still produce completely incorrect business decisions.
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Tools: Great Expectations, Soda Core, Deequ
Data quality validation is no longer an afterthought but a core component of modern data pipelines. This article explores three leading open-source frameworks — Great Expectations, Soda Core, and Deequ — that automate data validation, profiling, and continuous monitoring. We compare their architecture, integration capabilities, and practical strengths through empirical examples and real-world use cases…