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SUBMIT YOUR IDEAData quality checking is so important. Not just in audits. Thanks for this challenge, it certainly got me thinking about other areas to incorporate these same techniques.
To me this one was more frustrating than interesting because the first task was not well explained and the final three were extremely simple.
The first task is not terribly specific, so you have to figure out for yourself what "missing or unclear" information means and how it affects your formulas. This is the kind of situation where I would be going back to the requester and asking questions to be sure that I understood the requirements. And then, if possible, I would be asking a coworker to check my work.
I am not sure how the third input was intended to be used. Perhaps to get the column names?
I only really ended up with the correct answer because I could spot check 18 rows manually. If this were a summary of hundreds or thousand of rows then I might have had a much rougher time checking my work.
Learning
1. Can be useful to read the requirements in detail before you start. And then read them again. And again. And again. And ask questions. And check the outputs of individual tools.
2. Remember that some tools will sort the data without telling you. Here it did not matter until the end, and then it only made a difference if you want to check your answer visually.
Done!