![]() Good ‘ol fashion data wranglin’ of course. If you want to believe in the magic of Alteryx, the long answer is below (spoilers!): So how, then, did we get all of the festive data for the Santalytics series? Well, if you want to believe in the magic of Santa, the short answer is that his elves sent it all over to us and asked for help. We hear the adage time and time again – an analysis is only as good as the data behind it. Of which, you should have taken special notice of Willie Carr, who can be safely presumed as the devil:īig thanks to our #SANTALYTICS Part 1 participants team), the Data The wedgy giving, loogie hocking, terrors of the world. Once all the pieces above have been worked through you have naughty/nice ratings for each kid that correspond to their gift tier and exclude the last 5 groupings – the naughty kids. While the exact naughty order doesn’t matter (they’re all getting coal), the nice classifications could have been reversed to make more sense for the increasing degrees of niceness (note: this isn’t necessarily required, as the classification text doesn’t affect the present distribution – only the order, which should have been determined by naughty/nice score). Santa, despite doing this for centuries, didn’t have all his naughty or nice classifications in an order than could be easily joined (or, err, read).Once a score is calculated for reach Recipient ID, you can join each kid to their respective naughty/nice score and use the same Tile Tool approach (25 tiles, to account for naughty ratings) as the above.We used a little formula logic to make naughty actions negative in degree and summarized (sum), but there are other approaches. ![]()
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