VizWiz

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September 19, 2016

Makeover Monday: Data breaches are getting bigger and more frequent

7 comments

Several people have recommended Makeover Monday for the Project of the Year in the Kantar Information is Beautiful Awards, which I must admit is quite stunning and flattering at the same time. The suggestion for this week’s makeover came from Andy Cotgreave. We intentionally picked something from Information is Beautiful with the hope that it gets a bit more exposure. Shameless perhaps, but what can it hurt? This viz from David McCandless certainly deserves a makeover.


What works well?
  • The viz is eye-catching and definitely draws you in. There’s something to say for that.
  • The interactivity is fantastic.
  • Good filtering, colouring and sizing options

What doesn’t work well?
  • The bubbles move all around for no apparent reason.
  • There’s way too much overlapping, making it hard to identify any insights.
  • Whether something is interesting is extremely subjective. I wouldn’t make these same choices.
  • The viz doesn’t fit in a single view, requiring too much scrolling.
  • Not all records are included. I guess this was done for artistic purposes as David is known to do, but it distorts the message.

I decided to work on my makeover during my flight to Prague, thus imposing a time limit on me. I started by creating a view that simply shows the number of data breaches by year using circles. This basically flattens out the original.


While this shows the distribution nicely, I don’t love it. Next, I converted the circles to squares, hoping the result would be more visually impactful as the squares take up more space.


This is definitely better, however I don’t like how it doesn’t incorporate the records stolen in each data breach well enough for my liking. So I decided to add a dot for every breach in the data set and change the location of each dot to the number of records stolen.


Getting there…iterating is really helpful. This shows some of the outliers really well, but I feel like I’ve lost the distribution a bit. I decided to quickly open the data in Vizable and when I switch the view to records stolen by year, Vizable presented me this interesting view that shows the median and the distribution.


I really liked this so I decided to build upon it in Tableau. My final viz incorporates the view from Vizable, the distribution of each data breach and allows me to focus the story on data breaches that were hacks versus not hacks.

Click to view interactive version

I find this final view much, much easier to look at than the original and also it provides much better context. For me, context is key. Every visualisation you create should include context somehow. Why? Context makes it much easier for your audience to understand the story.

August 29, 2016

Makeover Monday: U.S. Companies Are Hoarding Trillions Offshore

9 comments

First, I must give credit for finding this week’s Makeover Monday to Jade Le Van. She’s a massive supporter of the work everyone has been doing in this project. Thank you Jade for finding this beauty from CNBC.


There are so many problems with this visualisation. However, the most egregious mistake is that the data is completely wrong. The author took the original data set, which has the total money held offshore by a company and allocated that same amount to every country that each country has an affiliate in. For example, General Electric has $199B stored in 18 offshore subsidiaries spread across seven countries. The author allocated $199B to EACH of those seven countries. That’s simply wrong!

What doesn’t work?

  • The data is inaccurate.
  • The pie charts are a ridiculous choice, especially when you show every single company in each country.
  • The companies aren’t sorted.
  • The size of the pies isn’t proportionate across the difference columns. In other words, they aren’t all based on the same range.
  • It’s impossible to find a company you might be interested in investigating.


What works well?

  • Nothing; the whole visualisation is a complete disaster.


I had a few minutes to explore this data set while on the bus home, so I opened up the data in Vizable. Within about 20 seconds I had two views that were far superior to the original.


Quickly and easily, I have a view of just how much money companies are keeping offshore and who they are in a nice, simple ranked list. Great! I already have something much better than the original.

Two more swipes in Vizable and I’m now looking at the companies with the most offshore subsidiaries.


At this point, I felt I basically had all I needed to tell the story in Tableau. I quickly reproduced the two charts from Vizable, then added a Pareto chart for more context. Lastly, I added some headers above each chart to tell a synchronous story.

October 21, 2015

Makeover: The Billion Dollar Startup Club

Today at the Tableau Conference keynote, Dave Story introduced the crowd to Vizable, the first time Tableau has launched a new product at its conference. I immediately downloaded it and have already built three simple charts that took no more than a few minutes each.

As a use case, let’s look at this viz from The Wall Street Journal.


This is cute, but completely ineffective as a design. Comparisons are nearly impossible. I copied the data from the webpage, saved it into Excel in OneDrive, opened Vizable, connected to the data, and built this simpler bar chart alternative, all in about 2 minutes.



Tableau has yet again gotten me addicted...quickly. I can see many great uses for Vizable already. Go download it and play. It’s completely free.