What did I learn from Tableau Conference 2016? (part 2)

What did I learn from Tableau Conference 2016? (part 2)

Part 1 was posted a few days ago here, featuring numbers 1-8. We’ll jump in at number 9.

9. Tableau is moving into data preparation.

With the announcement of a three-year roadmap followed by the developers on stage, Tableau announced a raft of new features large and small. These are all well documented now in a number of blogs (and Tableau’s own website here). As an aside – on the way is the ability to import from PDF. Wow! But the one I want to focus on is Project Maestro. This is Tableau’s name for a suite of data preparation tools within Tableau itself. As a one-man team at work, I spend a lot of time cleaning, manipulating, reshaping and pivoting, but high-end data shaping tools such as Alteryx are prohibitively expensive. This seems to be a direct rival, and on speaking to people who use Alteryx and the like, they have good reason to be worried! I’m excited to be able to have much more data-wrangling available within the visualisation software. It feels like a game-changer, and it’s likely to raise the game of Alteryx (other data preparation software is available!) too. I’m sure they’ll do things to stay ahead of Tableau’s data preparation capabilities.

10. An artistic solution is often better than a complex solution

Michele Tessari of Tableau gave a talk about Artful Data. I was expecting a session about nice artistic visualisations but I really liked the way he balanced the artful approach with the analytical. Best example was in calculating and displaying the median of a dataset. The string of complex calculations left most of us open-mouthed in complexity. And yet, set up a curve showing cumulative percent, and hey presto the 50% mark is the median. Done in seconds, more easily, just as accurate, and a clear example of the advantage of an artful visualisation over a complex set of calculations.

11. Make sure your visualisation stands up in greyscale

There’s so much talk in data visualisation about correct use of colour. For that reason, this one piece of advice from Andy Cotgreave (which I haven’t heard before) seems counter-intuitive at first, but makes perfect sense. If you have a well-chosen colour palette then it should be perfectly readable in greyscale (just black, shades of grey and white).

Rather than critique some visualisations out there, I’ve decided to put a couple of my own more colourful works under the proverbial microscope. Time to admit that the first one (a France tile map using a large range of pastel colours) has not worked well in greyscale. The second (a heptathlon-themed visualisation) has worked nicely in my opinion, with the full range from green through yellow to red distinguishable in the Overall Position column.

One out of two looks OK – perhaps I should go back to the drawing board with the France visualisation!

France tile map – some colours are hard to make out in greyscale
Heptathlon data visualisation – originally used palette of red, yellow and green


12. #VizForSocialGood

There were many separate sessions on a common theme – the idea of using visualisation for a good cause. Schedule clashes were such that I missed sessions about the work Tableau Foundation are doing to support non-profit organisations, as well as a great talk about the work of Tableau geniuses Datablick and how they are using tableau mapping to help eradicate malaria in Zambia. I didn’t attend that talk because I don’t really have experience mapping in Tableau, but have heard nothing but good from those who attended and those who have taken part. But in addition to this, the final gathering of the conference introduced the idea (and hashtag) of #VizForSocialGood (from Chloe Tseng/@datachloe again). I like this. As we continue to learn and improve, it’s important to work on personal projects you want to work on and enjoy (as I alluded to in the Steal Like an Artist section here). But I think that should include not just cricket, or music, or books, but important causes, especially as presence in social media networks grows. I refuse to use such a cringeworthy term as a New Year’s “Vizolution”, but it’s definitely on my list to do more of over the next year. And soon.

13. The Double Pivot

Another technical takeout here, which I won’t write too much about. I have to include innovations in survey data reporting though. Zen Master and leader in the field of Tableau survey data reporting gave a talk on new ways to visualise survey data given recent improvements in version 10. Most prominent was the “double pivot” –  a way to pivot demographic data and merge back with rest of the pivoted survey data. The upshot is a great way of showing traditional banners of demographic/dimension data. Survey data is my bread and butter professionally, so it’s raised some interesting possibilities for professional work. So it’s included in my list.

14. Let the Data Decide the Visualisation

Another tip from an Andy Cotgreave talk – is “Let the data decide the Viz.” I like to think it’s obvious but it’s such an important thing to bear in mind that it bears repeating. Particularly within the confines of an environment where you might be keen to try something new. You can’t just learn how to do a sunburst chart and decide you’re going to use it for your next visualisation. Data first, then visualisation type, not the other way round. Below is a very famous visualisation which Andy referenced – creatively and brilliantly set up to represent descending blood representing casualty numbers. But it only works so well because the data fits. Unnamed_CCI_EPS

15. A word on Tableau’s community

Leaving the best to last, but I have to be careful here. A few months ago, Ben Jones of Tableau Public wrote this excellent blog pos about building a thriving community: http://dataremixed.com/2016/07/building-a-thriving-community/ – in particular including this graphic


I said I need to be careful here – with the welcome I got from so many of the community at the conference I’m in danger of rolling down the back of the hill straight into the love fest! I can’t talk highly enough about the welcome I received. It seems that if you (a) do a lot of visualisations, (b) tweet a lot, (c) have a blog that people read (this one, believe it or not) and (d) are English, for added novelty value, then there are so many people to meet, and so many people who recognise you. People, some of whom I didn’t know but many of whom I admire, introduced themselves, shook my hand and just wanted to share conversations and experiences (and sometimes beers!). I thought of mentioning everyone here who I met who I spent time with and made my experience better in their own way. But it’s no exaggeration to say there are too many. In fact, much too many. And to single out just a few would be unfair. But you all know who you are, and thank you all.

Added to this was a genuine big surprise. Tableau Wannabe Podcast Hosts Emily Kund and Matt Francis host the “Vizzies” awards, for various categories  voted for within the online Tableau community. The (joint) award of “Notable Newbie” for me, presented on the final morning, was the icing on the cake for me. And it was a hell of a good cake even before then.

Here’s a link to Matt and Emily’s podcasts including one with more details on the Vizzies (I’m not sure the awards are published yet).

And here it is.


Back to Ben Jones’ blog post and diagram, it’s true the “love fest” isn’t the most constructive way for the community to grow. Perhaps we can make an exception for 13000 or so like minded people meeting face to face (this sounds bad doesn’t it?!). But I love the idea of “iron sharpens iron”. The result of the face to face contacts and friendships I made is that the number of people I can call on for constructive criticism as well as help and advice has greatly increased. I’ve already been pleased, since the conference, to be constructively talking to those I previously only knew tenuously. And I genuinely think that one week in the year spent talking about visualisations, meeting people and socialising (talking about anything but visualisations!) leads to the other fifty-one weeks with a stronger support network. Of course there’s no need to wait for national congresses – we are all encouraged to join local user groups and meet-ups, and I’m delighted to have taken part in the inaugural Birmingham Tableau User group already since returning from the conference.

16. And finally …

That’s it really – I could have a miscellaneous section on non dataviz-related weird and random stuff, such as (a) people take pigs onto planes from Austin airport, (b) a previous governor of Texas could have been my ancestor, (c) the giveaway squishy Tableau brains make great cat toys (and I admit that’s a touristy “Keep Austin weird” mug accidentally in the background, or (d) the local Voodoo do(ugh)nuts were amazing, even if shaping them into a “T” for Tableau was perhaps more suggestive than intended, but it’s not that kind of blog. Oh, go on then. Hoping to continue this blog series in a little under twelve months time from Vegas in 2017!



What did I learn from Tableau Conference 2016? (part 1)

What did I learn from Tableau Conference 2016? (part 1)

Last week, I had the great fortune to attend Tableau’s yearly conference, in Austin, Texas. In the interests of disclosure, I should say that my entry was paid for by Tableau, as winner of an entry competition. With so many sessions to attend, things to learn, speeches to hear and people to meet, I’ve tried to narrow down to a few key points. I failed, there are lots. Here are the first few of a two-parter, in no particular order:

1. Write the book you want to read / Write what you want like

This learning is the only one that is in a particular order, because it came from the plane journey. A couple of weeks ago, I recommended the concept of “Steal like an artist” – in doing so I obliquely referenced Austin Kleon’s book of the same name. It felt right that I should go one step further and actually read the book, so I purchase the book to read on the plane. I can thoroughly recommend the book for anyone who wants to think creatively in making data visualisations. The author is a creative person, an artist, who, by coincidence, lives in Austin, Texas, so reading the short book from cover to cover really gave me the mindset for the conference and upped my excitement level from day zero.


The quote I’ve chosen is simple – in looking to make an interesting and creative visualisation, think of yourself as the audience. The advice “Write what you like” is in direct contradiction to the usual mantra of “Write what you know” which is crossed out in the book. As an example, in traditional writing, you will write something much more creative and interesting if you write what you *like* (even if it’s science fiction, wizards and dragons) rather than what you *know* (your job, family and what you had for lunch …). That’s the mentality for creative visualisations.

2. Complexity is seductive

This comes from Chris Love’s excellent talk on the subject of simplicity. Keeping the mantra “Keep it simple, stupid”, i.e. KISS, he skilfully led us through the arguments for simplicity in visualisations. Complex is OK – if you’re trying to be noticed, win a competition or make your portfolio more visually attractive. But it’s rarely the best option analytically. In deconstructing a beautiful full multiple Sankey chart (below, original devised by Pablo Saenz de Tejada)


he showed us how insight could be better shown with simple histograms. I felt this was done with good taste and balance, since I’m a huge fan of the visual appeal and complexity of the original. A well-told story, not just for exalting the advantages of simplicity (which is an easy sell) but in acknowledging the balance.

3. Complexity is continuous, not discrete

Of the eleven breakout sessions I went to at the conference, when people asked me my favourite, I usually answered that it was Matt Francis’ talk: Bunking Data visualisation Myths. I would follow it up with the admission that it was probably the only talk where I didn’t learn anything new as such, but confirmed many of my thoughts on standard data visualisation arguments (are pie charts bad? should you never use red and green? etc etc). It was my favourite for pure entertainment – I’ve met Matt before and know he’s a nice charismatic guy (as comes across in his Tableau Wannabe podcasts). But I didn’t know quite how entertaining the talk would be – an hour of bad jokes and laughs at just the right point in the conference, great fun. I would thoroughly recommend a chance to watch Matt talk in the future, or at the very least listen to or catch up on any podcasts.

But on re-reading my notes from the talk I notice this gem that I wrote down – that complexity is continuous, not discrete. It follows on nicely from the point above and I like that a lot – there is no more an obligation to go for the flashiest possible an option than there is to keep the simplest possible option. The answer can lie anywhere on the scale from simple to continuous, depending on data, circumstances and so much more. In Tableau terms, it’s a green pill, not a blue one!

4. Positioning is important in how the user reads the dashboard

One of the most captivating talks was from Bridget Cogley – her expertise and philosophy is further demonstrated on her tableaufit.com website. In fact the full presentation she gave can be seen here: Bridget explained her background in ASL (American Sign Language) and linguistics as a background to her experience in designing dashboards. The results are always beautiful, but the importance of every consideration in a dashboard is every bit as important as grammar in the linguistics of a language. From a sound basis in correct grammar, the most beautiful and creative prose and poetry can be generated (not to mention the most technical and prosaic tomes too!). And from this background, Bridget made no apologies for showing us tweaks on the same dashboard dozens of time. From such an engaging and enthusiastic presenter (with the best trousers in dataviz) there was no apology needed.

Just one specific take-out was the importance of positioning and the consideration of Z-reading (shown below)


Our “default” way to read a dashboard follows the way we read text, and therefore we read in a “Z” fashion, unless of course we are reading in non-Western languages such as Arabic. It’s possible to position things in such a way as to draw our vision in a different fashion (perhaps the self-explanatory “N-reading”) but always consider Z-reading as the natural default.

I could have put lots of elements of Bridget’s talk as a headline, but possibly the key takeout message for me (let’s call it 4a) was

4.a. In interpreting, if your message isn’t understood, you’ve failed. Exactly the same goes for dashboards.

5. The “Crying” emoji was the most popular Twitter emoji in April 2015


Why is the “Crying” emoji the most popular in April? It turns out because a lot of people are very unhappy about doing their tax returns. How do I know that? Because Twitter use Tableau in many ways, both internally to monitor the progress of their analysts and the tickets they work on, and to record (sometimes fun) analytics about how people are using twitter. How do I remember that? Because I attended a session on how twitter use Tableau. In fact, this was the only customer session I attended, with all others being specific to features in Tableau or principles of data visualisation. But the real reason that answers the question “how do I remember that?” is the enthusiasm and passion of the speaker (Chloe Tseng). Quiet and polite away from the microphone, her enthusiasm, passion and humour shone through, whether in her daily work or the causes she believes in. It was a key example to me of the many ways in which data visualisation people (Tableau people in particular) are passionate about what they do and in sharing their experiences. It made me want to be as enthusiastic and charismatic as Chloe (and Chris, Matt, Bridget mentioned above) and talk at more gatherings and conferences, from the fun to the serious and technical.

Here we see Chloe talking about her work at twitter, possibly to do with emojis, but equally likely to do with the Lean Startup philosophy of designing dashboards internally where they try and minimise the number of administrative/iterative progress points in the design and creation process. The emojis and enthusiasm draw you in to the drier business message which in turn denotes a promising ethos for the future.

6. The US Election is a tricky time to hold a conference

“Avoid politics” was the general mantra – so many great visualisations had been done on the US election in the run-up to the week, but they were avoided so close to the event. I suspect that the US election date wasn’t considered when the conference was organised, with the result that election day fell right in the middle of the conference on Tuesday. Rightly, all US citizens had been encouraged to vote in advance before attending the event, but still the event passed with barely a word. But as votes were counted in the evening (and I watched in fascination in the evening on my phone in the bar in company of bemused and incredulous US delegates I now consider my friends) it became obvious that something very big and unexpected was happening. When you’re in the business of data, research and visualisation, it’s impossible to ignore the implications of the vote (I’ll devote a full post to it and will link to it very soon here once it’s written). But aside from that, speakers and delegates had to deal with a world-changing situation in mid-conference. Generally this was done with great dignity. The keynote speech the next morning was given by popular US radio scientific personality Shankar Vedantam  and although the psychology of decisions based on fear seemed particularly apposite, he kept respectfully on-meaage. The election and results were largely unmentioned except in good-humoured asides.

Outside, the streets of Austin were disrupted with protests which were small and good-natured. Political discussions were kept out of the limelight and life went on. Only the final keynote (from Bill Nye, Science Guy) went political. There was a little discomfort in his anti-Trump/conservative/evangelical views, but Bill’s pleading for future generations to use data to save the world were purely science and truth-based, and though not to everyone’s taste I don’t have a problem with that.

7. Tableau is moving forward with diversity, slowly!

I’m a white, English-speaking, male data nerd and was expecting to be in the company of an overwhelming majority of people like me. Now I don’t know what the figures are, but I was encouraged throughout to see the prominence of women. The pre-conference began with a Data+ Women meetup and when the keynote speech featuring five of the brightest young developers took place, four of the five were young women including Ethiopian-born Makari who seemed a brilliant star for the future. The line-up of Zen masters (the most talented Tableau users who do most for the community and users) remains largely male although the most recent intake has addressed this slightly, with three of the most recent ten Zens being female. Overall though, the line-up is largely white and male


Now this can’t change overnight and it would be unfair to “un-recognise” the great work and talent of the men involved, but the brilliant women I met suggest that the talent is out there. But the one place we really need to do something about it is in the UK. Our five UK-based Zens are all white, male, and similar in age. Let’s see some talented British women or non-white men there next year, Tableau!

8. Diagonal reference lines, starburst charts, mobile formatting charts …

This blog is getting long now – let’s end on a high, and a “more to follow”. I learnt so many new technical tips that there’s not enough room to include them all. I missed Andy Kriebel and Jeff Shaffer’s “50 tips in 50 seconds” talk which is now top of my list to watch on-demand. But despite that, Robert Kosara taught me how to use diagonal reference lines. Adam McCann taught me how to do a starburst chart. Dash Davidson gave a great “Jedi” tip on how to create mobile dashboards, Michele Tesseri showed us how to visualise median measures … the list goes on. These kind of tips are the nuggets that we all went to pick up to do our job better. The list is long, and the conference just kept on giving.

Part 2 will follow