You're involved in a business intelligence project, making great progress creating reports and cubes for analysis for your business users. They're excited about what they see and can't wait until they have the system up and running.
But then something happens in user acceptance testing. Some "funny" data values appear, and you can't aggregate the data or drill down correctly. You find the data problem and get around it, but immediately hit another anomaly. Pretty soon, the business users feel there is a severe data quality problem and your project goes from the stratosphere to crash-and-burn. What happened?
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