I probably mention Makeover Monday (or, to give it its twitter name – #MakeoverMonday) quite a lot in passing, so this is a post not just to explain what it is, but how it has helped me, both in terms of my skills and confidence in Tableau in particular, and in terms of becoming part of a flourishing (mostly) online data visualisation community.

So, a quick run down of the facts.

  • The initiative started in the first week of 2016, between Andy Kriebel (Head Coach, the Information Lab UK – @vizwizbi) and Andy Cotgreave (Tableau Evangelist – @acotgreave).
  • Every week, usually on a Sunday, Andy K will post (via blog and twitter) an original visualisation to be “made over”.
  • Some are awful, some are already great in which case the challenge is to present a different angle on the original
  • Some like to limit the exercise to a maximum of 1 hour, some don’t!
  • When complete, post a link to the visualisation and/or a picture, using the hashtag #MakeoverMonday
  • All the individual screenshots are compiled into one big Pinterest collage of combined visualisations
  • For more of the thinking behind the phenomenon, how it started, and all weekly original visualisations so far, see www.vizwiz.com/p/makeover-monday-challenges.html

I’m not sure when I first became aware of it. It might not have been in week 1, but it was certainly near the start.The first few were complex datasets where people, mostly (if not all) Tableau Zen Masters* would submit creative, highly-skilled works of art. It would be the kind of thing I wanted to aspire to (and still do) but I watched from afar, principally because the projects seemed not just a very high quality, but also large in scale

* simplest definition would be people who are good, I mean *really* good, at Tableau

Then, by week 7, I had a go. The chart was about video game usage, and I had the creative idea (for me) of doing pie charts that looked like Pac-Man and other measures that looked like blue dots. I even tried ghosts as lollipop charts. It sort of worked, used a bit of trickery, and gave me a “way in” – if I could do something new to the group, or new to me, each time, then it would be worthwhile. Looking back now I can see it wasn’t great but I was on my way.

pacmanI tried something new in Week 8 that was so bad even the usually encouraging Andy K replied with a “What the … what?” but was back on form relatively speaking for Week 9 and football wages. It was both bad and basic, using shapes in bar charts, but taught me something new, so I persevered. Week 11 had me trying a new map projection – having always hated Mercator, I now know, albeit by blindly googling and following another community blog, how to do a Robinson’s projection world map in Tableau.

Week 17 introduced me to a Sankey chart – something I’ve always wanted to try but not just for the sake of it. But this dataset worked and I was pleased with the result.

Week 18 introduced me both to a tile map for the first time (you’ll know from my last post how much I like using those now) as well as my first ever bump chart. I regularly refer back to this viz for one or other of these elements to remind myself how to do it – each viz was breaking new ground for me – see them both below (and click through for the online Tableau versions if you wish)

Trafficking

 

Tuition Costs

Week 19 was somewhat of a breakthrough. The quality and quantity of submissions was increasing all of the time, especially among those with real creative talent. Infographic-style submissions continue to blow me away each week and I feel privileged to be among the same group of participants as many of these people. I try and improve technically but I know that my creativity has its limits. Back to week 19, on the theme of climate change, I realised that, in the spirit of trying something new every week, I’d never actually used a heat map before. I chose a heat map submission, picked some cliche hot and cold colours, was pretty pleased with the “heat haze” effect that resulted, almost by fluke, and submitted the visualisation.

It’s not false modesty to say there must have been twenty or thirty better submissions that week with more insight, better creativity or both (we’re probably up to 100+ weekly submissions now after all) but somebody must have liked my creation because it was voted Tableau’s “Viz of the Day”, and a few days later became “Viz of the Week”. You know, the viz that stares you in the face on the right hand side every time you open Tableau? Yes, that one. I haven’t revised my opinion, there were still several dozen better submissions that week. But mine was good enough that somebody liked it and somebody chose it for acknowledgement. All of which confirmed what I suppose I already knew that you don’t have to aim for any type, style or quality of visualisation in the face of so many shining examples out there. With the right skill, software and encouragement (all three of which are provided by #MakeoverMonday) then you can produce something that someone will be impressed by.

Dashboard 1-2

I  won’t bore you with the rest of my submissions. Suffice it to say, I still enter every week and still try new things – sometimes I’m pretty pleased, sometimes I know it’s not one of my best. Sometimes the community agrees with me, sometimes it surprises me, either by liking something I wasn’t especially impressed with, or ignoring (relatively speaking) something I thought was really good! But there are now so many participants, many of whom will comment, encourage, commend, retweet, etc., that it’s really helped discussion flourish. I’ve left everything online though, so all of the entries can be seen in my Tableau Public page here: https://public.tableau.com/profile/neil.richards#!/

It’s possible that it’s been a victim of its own success – some analysis by Andy K of datasets downloaded versus entries submitted suggested that the standard of some entrants was so high that it was putting off new participants, and there was an element of disquiet that it was a shame for those who invested the most time and skill into the project to feel they had to rein it in. There was a resulting brief “Keep it simple” ethos which some have adhered to, and the number and standard of participants has continued to rise from all round the world. Certainly I see both sides of the argument and sympathise with the difficulties of managing expectations of something that now involves many hundreds of people every week. My own view is that the most important thing is for nobody to be intimidated, because everyone is welcome to take part if they want to at every level. Set your own goals – I know in my case I’ve done that every week and I’ve gradually improved, regardless of what others have done. My efforts have been every different standard between awful and not too bad inclusive, with all levels in between!

So what have I gained from #MakeoverMonday? In no particular order …

  • Technical skills (which are continuing every week. I have learned techniques which I now use professionally in work – bump charts and Sankeys had never been seen before introducing them recently!)
  • Support network (which is growing every week – so many people I can communicate with for assistance, debate or conversation about visualisation who have #MakeoverMonday participation as a common interest)
  • Confidence (growing all the time – enabling me to use new techniques and contribute my own experiences to newer users)
  • Friends (have had the chance to meet many UK experts in real life through user group and roadshow events with many more worldwide experts to follow in Austin this year)
  • Prizes / Swag (OK this one’s indirect – my climate entry persuaded me I am good enough to enter and win things, and now I am the proud owner of a T-shirt and a free conference entry ticket, the latter is a high value prize!)
  • Exposure (the #MakeoverMonday project is very well known now, not to mention this blog which I wouldn’t have started without encouragement from the community)
  • Publication (it’s still stunning to me that something a data nerd has done as a hobby for a year or so has been printed, published and featured in a French magazine, with full recognition and small remuneration!)

Finally – data visualisation expert and author Andy Kirk summarised his thoughts on the ten most significant visualisation developments of the first half of 2016 here in his visualisingdata.com blog. When an initiative is seen from outside and independently given high praise for its significance in the field you realise the magnitude of the project. Certainly for me, it’s been a handy coincidence though that my own journey using Tableau in particular has more-or-less coincided with Makeover Monday. And it’s been a privilege to be part of it, long may it continue!

 

 

 

 

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