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Dashboard Week | Challenge 4

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Day 4 of the dashboard week. It’s the final stretch til the end of the week! Yesterday we had an enjoyable graphics design challenge and today we received a much more difficult challenge. Here are the rules:

  1. Choose one or more of the 3 datasets provided
  2. Create a dashboard with the datasets selected
  3. Must use at least one external source of data to enrich your dashboard.
  4. NO ALTERYX allowed.

Not being able to use Alteryx is a big challenge provided that we have used Alteryx almost every week for the past 14 weeks. Really had to take out the thinking cap and use Tableau logic in Tableau Prep and Tableau to do the calculations.

The problem

For this challenge, as soon as I heard what the datasets was about, I knew what type of story I wanted to build. The data was on solar energy. We have 3 dataset, small scale installation data by postcode, large scale installation and a single household energy generation data for 10 years. Based on the story I wanted to tell, I selected the single household energy generation data. However when I heard that an external data source is required to enrich the data, I was in a stump thinking on what data to add in. In the end, I decided to add average household information in however I spent a lot of time trying to find extra data but i couldn’t. The best I could find was information provided by comparison website, those that try to get you to change energy plans. So that was a struggle. Once I got what I wanted, I used Tableau Prep to join the data.

Once I had the data i wanted and started to work on it, another problem occurred, I realised the aggregation of the data is at a different level so I wasn’t sure what chart i should build that would best tell my story. In order to tackle this problem, I decided to approach it from a different way. Compared to my previous dashboard which are considered explorative dashboard, I decided to create a story dashboard. It’s the type of dashboard that doesn’t require navigation to tell a story. It’s self-explanatory just by looking at it. And this is the final product:

Personal Feedback

Provided I had more time, I most likely would have done a better job. There are some parts where I wish I could visualise to tell a better story but failed. Overall, I am happy with the final outcome. Note to self, things that look easy may not end up being easy.

Check out my viz here.

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