Do we take data visualisation too seriously?
It’s been a while since my last post – there’s a good reason for this. Well, a reason anyway. I have a 90% written post which I have been mulling over for a long time. Because I haven’t felt comfortable with it, or finished it, it’s been a bit of a logjam for the blog (a blogjam?), with subsequent blog posts and ideas taking a back seat. So, rather than abandon it, I’m going to smuggle that post, untitled, into the next two paragraphs, then move on with this post. Let’s make this blog more about data visualisation, and questions therein, than about me. The eventual point to this post might not be clear until much nearer the end – stick with me!
The title of the aforementioned previous post was going to be “So how on earth did I become a Tableau Zen Master?” because last month, that happened. You can learn more about the Tableau Zen Master scheme here and the three elements that comprise selection to become one: Master, Collaborator, Teacher.
I’ve done a lot of thinking about it – it really has left me scratching my head for a few weeks despite all the congratulations and positive comments I’ve had, and I’m still not sure I know the answer to the question of how I became one. But I’ve started do get through the impostor syndrome and I’m going to embrace it. Though I can’t mention impostor syndrome without linking to fellow Zen Bridget Cogley’s post about it – just promise me if you read it you’ll come back here. Get engrossed in her blog and you won’t feel the need for mine or any others … Anyway, there are only just 30 Zens in the world, and I know that I am not one of the top 30 most technical users (I don’t know how you’d quantify it, but I’m patently not even anywhere near the top several thousand). But I’ve come to realise it’s about more than that. I have to assume that people respect and like what I do and the manner in which I do it, share it and evangelise it. And more often these days I’m seeing amazing work which adapts and improves on mine, with three crucial words that I’ve grown to love: “inspired by @theneilrichards“. Hopefully I can embrace it with humility, because even by cutting a long introspective blog post down to two paragraphs I can still leave enough space to say a huge thank you to those who nominated me and those in Tableau who appointed me a Zen Master. Those who have given advice have all essentially said the same thing, to me and to all new Zen Masters: “Keep doing what you’re doing”. So, I will. For me, that’s visualising a lot, speaking a lot, and blogging a lot.
So, perhaps as a result, I’ve been prolifically visualising. Two visualisations followed around last month’s Winter Olympics. First of all, my response to a #MakeoverMonday challenge to visualise historic medallist data was this joy plot below (and here’s more about joy plots)
Hot on the heels of that was my curling-themed visualisation, which I’m obliged to figure and self-promote, because it has been featured as Tableau’s Viz of the Day
Both of these are example of the direction in which I’m continuing to head (especially in the visualisations I choose to promote, anyway) of design driven data. Focussing on design elements first and choosing the data, whether it be the overall dataset or the elements within that dataset, to represent the visualisation choice. The joy plot in particular was a case in point. Partly liked and partly disliked/overlooked, I had one comment which described it as a beautiful work of data art. That continues to be my aim, and because I don’t claim it to be an analytical piece, that’s the feedback I can choose to included while ignoring those who dislike its analytical weaknesses!
The curling visualisation has received a bit more acclaim and is another example of design driven data that I’m really pleased with.
