Who doesn’t love a map? For week 22 we looked at global internet users across almost 200 countries. Andy and I both had a fair bit of critique for the original viz and I am very pleased with the numerous great submissions from the community.



What was great to see were the high quality visualisations which managed to either do completely without a map or used a map very effectively to enhance the data story around internet user numbers.

There is also definitely a trend towards more simplicity and vizzes across the Makeover Monday community are becoming simpler and clearer. It’s great to see that the feedback we give as well as the comments many of our community members are contributing on Twitter on a daily basis, have helped everyone to improve their work and tell better stories with data.

And a non-data related development I have noticed that I’m excited about is that the regular members of the community seem to really have gotten to know each other. It’s almost like we’re working together several days each week and people are starting to recognise each other’s style and preferences and can tell by the image of a viz who the author is. The tone in which everyone is talking to each other, giving tips, answering questions, making suggestions and encouraging newbies is really supportive and friendly and a very positive reflection of the greater Tableau and dataviz community. I wanted to say thanks for being really cool people and for making this project a positive learning experience for everyone who gets involved.

We’re really looking forward to meeting many of you in person at next week’s live Makeover Monday event during TCOT London.

Now let me share a couple of lessons from this week’s challenge.



Yup it happened again and I’m just as guilty of using it during my analysis of the data. The dataset contained internet users per 100 people, which means it was essentially a percentage. An average number per year per country.

The data is at the country level of detail. We could go up to a regional level by grouping the data, or even a global level by taking the average across the entire dataset. But that’s a bad idea. Why? Well, we are not considering the weighting that went into the underlying data, e.g. the population of each country in a region.

During my viz process for this week’s makeover, I initially did this wrong, but Andy gave me some feedback, so I fixed it before submitting. Reminder: get feedback from others, and feel free to ask them before publishing.

There has also been a discussion about it on Twitter this week and Andy pointed out that he went about it the wrong way, too.

If you averaged your averages, check your viz to see what the numbers are and ideally fix it to show the right results :-). Check out Charlie’s blog for a great explanation.


My recommendation: Always check at what level of detail your data is captured. Ask yourself whether your aggregations are correct and a sensible way to represent the data. Ask others for their feedback on the way you treated the data.

It’s not a crime to do stuff wrong, so don’t be discouraged if you made a mistake. Just make sure you learn from the collective work of this community and if you don’t understand why what you did was wrong, then ask.



This isn’t something wrong as such, it’s more a matter of preferences and my attempt to encourage you to try something new.

We tend to see a few submissions every week which are very much traditional BI dashboards. There’s nothing wrong with building those dashboards but often they are not as engaging as they could be. Partly that’s because of the layout and people being so used to the ‘KPI dashboard’ look and feel that they don’t really engage with the content.

But also, these BI type dashboards we see being submitted often appear to be a collection of charts that are not strongly tied together through a story and don’t have a natural flow to them.


My recommendation: Be bold and try a different layout. If you want to have multiple charts in your dashboard, why not go for a tall portrait layout and have the charts follow each other to tell a story? They don’t need to be in a 2×2 matrix.

Add some text boxes in between to break up the view and provide content as well as connect your visualisations within a bigger overall story.

Now let’s look at the favourites for this week…




Neil Richards

Author: Neil Richards
Link: Tableau Public

What I like:

  • Neil’s design is clever, thoughtful and unique. You can tell that he considered a number of factors when putting this together, including context, colours and layout. It’s great to see that effort translate into a beautiful and well executed viz
  • Despite the ‘behind the scenes’ work that went into the tiled map, the viz looks simple and effortless and the data gets to speak for itself
  • The data tells a story through design and colours. No additional text needed.
  • The legend contains enough detail in each map to help me look at the years in isolation as well as the bigger picture
  • The colours are well chosen and the font is nice and simple to balance out the structure of the design
Alicia F. Bembenek

Author: Alicia F. Bembenek
Link: Blog

What I like:

  • Alicia’s viz is simple and compelling.
  • The black background works well for the topic of ‘Internet’ and the colours chosen for the circles look good on black
  • The title provides good context and tells me what I should look for, i.e. a pattern that is consistent for the countries. So I am expecting some sort of visual grouping of the data points
  • And alas, the dots that are grouped vertically by year (colour) shift together to the right as they change colour and size. Clever!
  • I really like the font Alicia used and the uncluttered design of her chart, no unnecessary lines or labels
Steve Wood

Author: Steve Wood
Link: Tableau Public

What I like:

  • Steve’s viz is simple and neat and he went through a couple of iterations to get to his final viz after receiving questions about it
  • The maps are a nice way to provide context for his overall message
  • Focusing on the top 5 countries by highest proportion of internet users gives the viz a good story
  • The colours work well and in combination with grey stand out very nicely
  • Steve identified the issue with filled maps and instead of avoiding it, tackled it and provides a lesson for all of us that he included in his viz
Michael Mixon

Author: Michael Mixon
Link: Tableau Public

What I like:

  • Michael’s design is outstanding. He very effectively combines small multiples of sunburst charts with a great colour scheme, a regional structure and a view across time. In one chart.
  • The viz is engaging and makes me want to explore. And instead of giving me the overwhelming task of picking a single line, I’m just encouraged to select a region to get more detail. So I do and there’s a whole lot of additional information provided
  • The detail of the additional information is great and the way it is presented makes it accessible for the viewer
  • At any point I have the flexibility to return to the starting point which makes me more likely to interact more, rather than getting stuck and just leaving the page
  • The context provided helps me understand the data from different angles
Ulrik Willemoes

Author: Ulrik Willemoes
Link: Tableau Public

What I like:

  • Ulrik’s viz has a simple design, uses colour effectively and tells a story
  • Nice big call outs on each panel support the story and give the viewer the necessary context
  • Colours are meaningful and really show the changes over time
  • Going in increments of 5 years is a clever way to get around the gaps in the dataset
  • The bar chart accentuates the context provided in the text
  • The grey and purple combination works really well
Miguel Cisneros‏

Link: Tableau Public

What I like:

  • I cannot end the week without talking about Mike’s viz. This is stunning work.
  • This kind of design draws me in and makes me want to interact with the viz, so I went to Tableau Public and clicked around
  • It’s not just visually compelling but it also tells a story, the story of progress for each of the countries included in the dataset
  • While there are other and simpler ways of conveying the information, it is a great example of what’s possible in Tableau and it will hopefully serve as inspiration to the community to try a few different things.