Makeover Monday, week 17: Data skills are in huge demand

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For week 17, our friends at Tableau Software have joined the Makeover Monday party and have provided us with a viz for our makeover. Not just that, but they have also written a blog article on the topic of the demand for data skills while encouraging their community to get involved in our project to grow and improve their Tableau expertise.

We’re stoked to have Tableau join forces with us to help more dataviz enthusiasts get better in their analysis and visualizations and to help us welcome new members in our Makeover Monday community.

So what are we looking at this week? It’s data from LinkedIn’s Top Skills Report (2014, 2015 and 2016) and the viz was created by Tableau’s Marissa Michelotti and published on Tableau Public.

Top Job Skills (1).png

What I like about it:

  • The title is specific and tells me very quickly what kind of content and information I can expect. Not only does it suggest to me that I will find information about specific skills (maybe a list of sorts), but by having the title as a question it immediately engages me and makes me think about the answer I expect to find
  • The dashboard is tidy with a clean font and a limited number of filters
  • The filters are useful and the titles instruct me on what I can use them for
  • The box and whisker plot at the bottom tells me to ‘Explore’ the top 25 skills, which does make me hover and click to see what else I can find out from the viz
  • Listing each year on rows in the box and whisker plot helps me look at how the demand for specific skills changed over time


What I don’t like about it:

  • I always like having a bit of context with a brief description of the findings or the underlying data. I’m missing that here. I’d appreciate to read about the LinkedIn report and maybe some surprising or unexpected insights, an introduction to the topic.
  • While the title tells me a fair bit about the topic to come, it is very broad. Are we looking at skills for the Data industry? Or for jobs in general? Is this limited to professionals? Does it only include jobs that require tertiary education? Essentially: Should I even look at this viz or is there something about me that means the findings aren’t relevant to me?
  • While I like the idea of a bump chart, the colours don’t add much value for me, because there is no legend, so to make it more intuitive, I would prefer colour choices that communicate ranking, e.g. a gradient that has dark colours for skills in high demand and light colours for lower demand.
  • The box and whisker plot would benefit from an explanation. Many viewers don’t know how to read a box and whisker plot and it would be great to guide them through the chart so they understand what it shows
  • The box and whisker plot has a title telling me there are 25 top skills, but with the filter this number is reduced. I would prefer the title to be more specific so it’s clear that my filter gives me a subset of those 25 skills


What I did:

  • I decided early on that I wanted to create a mobile friendly version and make the data personal for the audience. I felt that in order for them to identify with the topic and get more value from the LinkedIn findings, it would have to be an interactive viz that is relevant for the user
  • The data gave me two obvious approaches: a skill-based and a country-based view, i.e. letting a specific skill drive the data or starting with a country
  • I wanted the user to use filters to select the skill and country options that most appropriately reflected their situation and show them where they can go with their skills or what they should add to their skillset to have better job opportunities in their country of choice
  • Keeping it simple was a key focus, so bar charts were my go-to viz option, as well as some text elements to provoke interactions. Questions were aimed to address the user directly and get them engaged
    • The bars are longest for the most demanded skills, because this seems intuitive to me.
    • I created a calculated field that essentially reversed the Rank value so that the bar length was easy to achieve
    • Putting the labels inside the horizontal bars was done to save space in the vertical mobile layout and to make the data stand out
  • A simple colour palette with highlights was used. But why yellow? Well, the data was about data skills, not so much about LinkedIn, so I decided not to use the LinkedIn colour palette.
    Choosing yellow was a personal preference that comes down to my little quirk of having synaesthesia. To me, the word data sounds and looks yellow, a warm, golden yellow. And that’s the only reason why I picked that colour for this week’s viz. The letter a in my mind is yellow, there you go :-).

(Click to view interactive version on Tableau Public)

What if....png


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