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Every morning the analytics team opens a report of yesterday’s orders. Your job is to design the pipeline that fills it. Overnight, raw order files land in cloud storage. Read them, clean them into one table the team can query, check the data is right before anyone sees it, and make sure a person is told when a check fails.
Find the deadline the business actually has, then buy the cheapest freshness that hits it.
Run the review to check your architecture against this scenario — a valid DAG, a trigger for the freshness SLA, a transform stage, a quality gate before publish, and a failure path — then defend it in a short interview.
This scenario runs a full workspace — editor, canvas and results side by side. It needs a laptop or desktop to be usable. Open this page on a bigger screen to start building.