More Data Quality Checks Make Your Pipeline Less Reliable

The case for deleting half your data quality checks

Every data team believes the same thing about data quality: more checks means fewer incidents. So they add one for every bug that ever burned them, every column an executive once questioned, every “what if the source changes.” Six months later the pipeline is wrapped in 200 expectations, and it pages the team more often than it did the day it had zero.

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