My latest Huffington Post article (published Wed 28 Jan) discusses how amazing our visual system is at seeing very granular levels of detail. Here’s a rather shaky GIF of the different views going from 1 data point to over 10,000:
The inspiration for the column and this post was Ann K Emery’s 2015 data resolutions. I’ve always been a big fan of small multiples, but her specific statement to “do more small multiples” triggered my efforts to break the data out of the charts I’d been making with the Citibike data.
There have been lots of posts celebrating small multiples recently. My favourite is “A Big Article About Wee Things” by Propublica. Go read it! Go on.
What I really need to emphasise is that no single view is the “right” one. Theere’s no such thing as the “right” view. Being able to cycle through these very quickly in Tableau is immensely powerful – each view teases something else out of the data as you feel your way to insight. Each view shows something different and if you can see 30 views in 5 minutes, who knows what insights your data will reveal? What’s certain is that we can reflect on just how complex and yet clear 10,000+ marks appear:
I’ve got this idea for a future theme looking at “3 ages of data viz”. I want your thoughts. Is there something in this idea? Am I right? Are there more? What’s the NEXT age going to bring? What does this teach us about dataviz?
Age 1: The Excel disaster (pre 2000)
The early spreadsheet designers got excited about graphics and gave us 3-d exploded pie charts. If only they’d read some theory about effective dataviz maybe we’d not have had 35+ years of fighting back against dataviz disasters. To be fair to Excel, as you can see above, the defaults weren’t really that bad, given the limits of graphics cards in the day. Unfortunately, people got too excited about the 3d options.
Age 2: the Stephen Few fightback (2000-2010)
Stephen Few took on the spreadsheet behemoths in the first decade of this century. He made us all see sense and put science-backed best practice on the pedestal. People saw the light and visual tools began to ditch the dross in favour of charts that actually work.
Age 3: the creative years (2010-present)
The problem with Stephen Few’s approach is that people found his approach, well, boring. Unarguably his approach was functionally correct and just right for operational business dashboards. But many people were left unmoved. They found that following his approach didn’t engage people. As data journalism flourished and infographics exploded, there was a realization that a balance needed to be struck.
At the extreme end we found that people like David McCandless found success with their design-trumps-function approach but others, such as Alberto Cairo (see his Tapestry Conference slides) and Andy Kirk (8 hats) pushed the need to ENGAGE as well as INFORM.
Tell me your thoughts
My ideas are fluid around this. I’m trying to make the point that we’re in a great place with the combining fields of creative power and effective design. What else do I need to know?
I paid for my first Tableau license 7 years ago today (15 Jan 2008). To say that changed my life is not an understatement.
I was a struggling data analyst using outdated, unsupported, inflexible BI tools provided by an underfunded, overworked IT department. I had a team of people who would spend 3 weeks producing 1 report for 1 faculty at the University of Oxford.
In desperation I searched the web for anything that might help me escape these shackles. I found this post by Stephen Few and clicked the link to this small software company’s website.
By the end of that afternoon, I had produced more useful analytics than we could do in a month. That was the afternoon my life changed. I put together a use case. Here it is:
Note that one of my risks is “not enough functionality” (this was v3.5). That was true but what it did was better than any single piece of software I have ever used. The great news is that Tableau is now a super-powerful machine.
Note also that the notes are written on an Oracle notepad. Ha! Take that, Oracle!
Looking back on my initial work, I am amazed I was pleased with what I was producing.
My experienced eyes see these views as unsophisticated and untidy. But the emotion I remember at the time was one of joy. I was playing with my data. I was asking and answering questions as quickly as I could think of them. I was unleashed.
I stayed at the University of Oxford for 4 great years. Over those years at Oxford, I began blogging, organised the first Tableau user group, and spoke at Tableau conferences. I was having more fun using a piece of software than I could have imagined.
You’re not supposed to enjoy using business applications. That’s just wrong. But this was FUN. So much that I would use Tableau at home for personal projects. Can you imagine using other BI tools at home for fun?
It. Just. Doesn’t. Happen.
In 2011 Tableau was growing in Europe and I joined the company; it’s 6th European employee. My first desk was shared with a photocopier. It’s been just as much fun ever since and I am grateful to have had this opportunity. I’ve made amazing friends at work. I’ve travelled to amazing places. And I’ve been inspired by the incredible community this product has produced.
I now get visibility of the product roadmap – I am very confident the next 7 years are going to be as amazing as the first 7.
What was your favourite music of the year? I thought I’d take a data-driven look at my listening habits, by downloading my last.fm data. I’ve found 3 interesting stories:
My favourite album: Gabby Young and Other Animals
We saw Gabby Young at the excellent Just-So festival. What knocks me out is the enjoyment in her show and her recorded music. There is such joy in the recording that you can’t help but get carried away. Her voice is exquisite and carries me away.
Two things the data told me:
I had a crazy week in November when I listened to over 200 Gabby Young tracks.
The tracks I most listened to are I’ve Improved and Fear Of Flying. Here’s the videos:
In any given week I’ll be listening to classical, or pop, or even deep filthstep but one thread that has been consistent through my life is heavy metal. You can’t beat a good scream and thrash every now and then. My top metal bands of the year are below.
Metallica remain the band I go back to the most. Check out that huge spike in August – 66 listens in one month. What’s interesting is that I got a little bit reobsessed with Anthrax in the same month – over 100 listens in one month. That was all about “Sounds of White Noise” – a favourite album from the 1990s and rediscovered and obsessed over in the Summer.
Meshuggah and Hatebreed make their appearance too as they were the only non-festival gigs I went to this year. Also the first heavy metal shows for, um, 20 years, I think.
Pink Floyd is number 2 most listened to for 2 reasons.
First of all, they released a great new album. I listened to it a lot when it came out in October.
The second reason is the spike in May. At this stage, we’d listened to so much Frozen I wanted to reset my kid’s music tastes! We listened to The Wall a lot – the kids like the talking voices. Here’s the same chart, highlighting Pink Floyd:
What did you listen to?
To make these charts, I scrobble all my music listens to last.fm. I then use Ben Foxall’s (@benjaminbenben) LastfmToCsv service to download all my data. Finally – I point Tableau to the data and explore away.
In the column, I link to lots of routines but I wanted to highlight Lennart Green’s TED talk in particular. I have watched this many many times – it’s mix of patter, sleight, misdirection is just perfect.
What’s your favourite routine? Or your favourite magician?
A light bulb moment this morning. When you label marks in Tableau you can choose ALL or HIGHLIGHTED. Sometimes you want to label the marks by default and highlight the labels when making some selection on another part of a dashboard. But you can’t by default – the “Marks to Label” option only allows one choice:
Can you work around this?
Yes – you can, with a dual axis chart. Duplicate the Measure on the Rows shelf and make it Dual Axis, with synchronised axes. In my example, I duplicated Profit:
Then I set one label to be All and the other to Highlighted:
Now you can build a dashboard which shows all Labels and has a highlight lable when you interact with other views in the dashboard.
Check out the interactive dashboard below to see it in action:
USA and Russia dominate the Olympic Medal tables but is that simply because they are large countries? Are there countries who get more medals per million people in their country? Yes. Check out the dashboard below:
Over the past month, I’ve deconstructed a dashboard I made for Tableau’s internal VizWhiz competition. Below is an attempt to quantify the Impact and Difficulty of each of the design choices I made. You can click on each one to go read the post describing the design choice:
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Why did I bother changing a dashboard that looked pretty fine in the first place? Why did I write 14 posts about this single dashboard?
Simple: I wanted to really think about the design choices and share the process of taking a perfectly functional dashboard and trying to make it into a thing of beauty.
Stepping back made me realise how many and what type of choices I make. Each choice has a highor low impact and is easy or hard. I quantified that in the viz above. As Michael Mixon pointed out in a comment, as we become experts we take this stuff for granted.
You are fighting for viewers’ attention with any visualization you produce. One of the few things you can guarantee they will look at and process is the main title. Therefore you better be 100% sure this is both:
Explains the chart or asks a question
Your title is your one chance to grab the reader and convince them it is worth focusing on. This is not a new lesson: Willard Brinton was talking about this 100 years ago:
Subtitles are just as important. Consider the titles on each view:
I’ve numbered them. This helps guide the user through the view. Sure, the left-to-right nature determines the flow but numbering the titles helps.
I bolded the pertinent data-related facts. I’m using the title to communicate the data itself.
I’ve also added contextual text. Notice the “All” in the second view title. If you filter down to a single year in the highlight table (you can do this in the interactive version), “All” changes to the relevant year: To learn how to make dynamic titles in Tableau,click here to see a post on The Information Lab’s blog.
Annotate marks to add context
Imagine I’d left the annotations off the charts. You can see the effect above. What are you left with? A chart with a really interesting trend that gives no clues as to what causes it. The viewer is left with their interest piqued but with no answer. This is a serious failure. Adding the annotations answers those initial questions.
My first iterations of this dashboard did not have any annotations. It was only when I got feedback from people that they pointed out the problem. That’s the importance of getting feedback!
Below is the annotated time series: it’s much more useful:
My final word on these annotations – I deliberately aligned the annotation arrows to be vertical to give them consistency
Tooltips – ALWAYS be customizing your tooltips
Followers of this blog will not be surprised that all the tooltips are customized. If you want to know more about the importance of tooltips, and techniques to use them in Tableau, check out this series of posts. Summary: ALWAYS customise your tooltips; it is the easiest way to improve your dashboard.
Finally, don’t forget to turn off the command buttons: these are great for exploration in Tableau but a distraction for end users.
I’ve only considered a tiny set of considerations when using text in your visualizations. What else do you consider important for text on your visualizations?
Come back tomorrow for the final post in the Tableau Design Month series – a big wrap up of everything I’ve covered.