Trace the Data Journey Before You Transform

Why this matters This lesson focuses on data journey mapping. In data engineering basics, the important move is to treat a pipeline as a product with a customer, a contract, and an operating model, not as a loose chain of scripts. The cited framework gives you a way to make that practical: name the business event, declare the grain or contract, make the transformation reproducible, and put checks close to the point where bad data can enter. The mechanism is simple but powerful. Pipelines fail when context is implicit. A column called status looks obvious until support uses it for…

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