Preppin' Data

This week on Preppin’ Data we once again had you all serve as labour for Chin & Beard Suds Co. It was quite a tough one! In order to overcome this challenge, our method uses a number of techniques from previous challenges. We mentioned at the bottom of the requirements that we used the Rows-to-Column pivot and another key hint provided was: although you had five questions to answer they can all be answered using the output data-set provided. What is this hinting at? Using the Profile Pane to answer questions! Before we dig into a few of the main challenges in the workflow itself, let’s take a look at the answers to the 5 questions themselves. 1) Whilst we can see both bar and liquid soap has been stolen in similar frequencies, the liquid soap has been stolen in much greater quantities. 2) & 3) We can see that 19 items of stock haven’t been updated yet: 5 in 'Wimbledon 2' and 14 in 'Oxford Street'. 4) The only store to update its stock in 1 day o...

Welcome back for the solution of week 4’s challenge! I wouldn’t put money on this being the last basketball themed challenge so don’t fret if you’re worried that this’ll be a one-time topic. Whilst this week did require some data preparation, the challenge had the unusual goal of using the Profile Pane to recover answers instead of generating a whole workflow to get there. The aim of this was to demonstrate how versatile the Profile Pane can be for quickly generating answers to questions that could otherwise require multiple cleans, pivots, aggregations, etc. To this end, we’ll highlight a few of the cool functionalities of the data pane that could have come in handy for you for our challenge! However, firstly for the impatient among you just looking to check your answers, here they are, but I’d recommend continuing reading to learn more about the functionality used: Our workflow demonstrating a possible solution. Q1. In games won by the Spurs, which player most often scores...