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How do test the upstream data is good in an etl process (etl testing part 3)?

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In the first two parts of this series (https://the.agilesql.club/2019/07/how-do-we-test-etl-pipelines-part-one-unit-tests/ and https://the.agilesql.club/2019/08/how-do-we-prove-our-etl-processes-are-correct-how-do-we-make-sure-upstream-changes-dont-break-our-processes-and-break-our-beautiful-data/), I talked about how to unit test your business logic and integration test your ETL infrastructure code. Having these tests ensures that your code is in order, it means you have documented, and future-proofed your code which is a fantastic thing to have. What testing our code doesn't give us is a way to validate the data we receive is correct.

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