Preppin' Data

Solutions by Jenny Martin & Jonathan Allenby and you can download the  full workflows here .  This week we were looking at de-duplicating and updating our training attendee data. In this challenge we mentioned that you can use Prep to avoid having to use LODs in Tableau Desktop, especially as Prep is so great at de-duplication using Aggregate steps. However, if you're comfortable with LODs then you can use them within Prep where it is more manageable to track and modify your changes. In the first solution, Jenny demonstrates how to avoid these LODs completely and in the second Jonathan shows how you can use LODs to achieve the same outcome. Both solutions are valid and which one you gravitate towards will likely just be a matter of personal preference and instinct. Solution A : No LODs Step 1 - Getting the current Account Managers and IDs In order to avoid LODs and table calculations we're going to make use of the Aggregate and Join steps in order to summarize and update o...

Challenge by: Jenny Martin Have you ever been working with a dataset in Tableau Desktop and noticed some duplication occurring? Of course, this is something you can fix with some potentially tricky LODs or Table Calc filters, but wouldn't it be nicer for your dataset to be viz ready before heading into Desktop?  If you attended the Tableau Fringe Festival last year, this concept may feel familiar, as I did a quick demo explaining why I, personally, would prefer to use Prep to solve my duplication issues. You can find the video here  if you like. Input The dataset we'll be working with for this challenge follows the same theme as the Fringe Festival. We have information relating to which of our Clients are attending our training sessions. Also included in our dataset is which Account Managers look after which Clients. However, we have historical information about Account Ownership which is leading to duplication. So how can we fix it? Requirements If you're new to the techni...

Data is everywhere and often in annoyingly small files that we need to piece together before we can begin analysis; Chin & Beard Suds Co is no different. This week's challenge is to piece together data we have received from our Clapham and Wimbledon stores. We've heard there are lots of differences between our two stores in South West London for Sales Volumes and Values. We've heard there are duplicates in the dataset so help us remove these as the entries are the same, just doubled up due to some reporting issues. Requirements Input all Data Files Remove Duplicates (identical rows) Work out the percentage of: Scent sales per Store's Total Sales Values and Volumes Weekday sales per Store Total Sales Values and Volumes Replace Weekday with full date Output Data Output Two Files: 1. Scent  - 20 rows (21 rows including headers) - 4 columns: Store  Date Scent % of Store Sales Volumes Scent % of Store Sales Values 2. Weekd...