Bananarama

On last week's episode of the Tableau Wanna Be Podcast with Emily and Matt, Jewel Loree shared that her go-to strategy for developing a new viz was to think of the name first and go from there. I thought I'd give this approach a shot, and for some reason the word 'Bananarama' came into my head - maybe because I like bananas or maybe because I subconsciously love 80's pop music. Who knows.

So anyway, here's a viz on the worldwide banana trade, with data taken from http://faostat.fao.org/.

The most interesting thing I see here is what's going on with Belgium - lots of bananas go through Belgium on their way to Germany.

Making 'Dieu et mon droit' and some tips for using Wikipedia data

The last viz I made, see below, was all about the history of English Kings and Queens. And the data source for that viz was a Wikipedia list page http://en.wikipedia.org/wiki/List_of_English_monarchs.

Now it just so happens that the next Tableau Public Iron Viz feeder contest is all about making something with Wikipedia data. So although I'm not going to be entering my viz, I thought it might be a good opportunity to write a few things about how it was made to show some of the things you can do with a simple Wikipedia list. And in fact if you look across my blog, you might notice that a healthy proportion of the vizes I make have taken their data from Wikipedia.


So on to the viz:

The idea came from three places. First I really wanted to collaborate with my friend Dan Miller on something. Dan is a great illustrator and calligrapher and I wanted to bring in some of his expertise to help produce a viz that contained some custom artwork. Secondly, I was feeling a bit homesick and wanted to do something with a British theme. And thirdly I was browsing Ben Jones blog and came back across this viz of US Presidents in the form of a Gantt chart which is rather excellent.

So it hit me, why not copy Ben's idea but do it for English monarchs? This would also enable Dan to bust out some sweet looking calligraphy.


So first I went off to Wikipedia to see what data they had, and as usual it was perfect for my needs and in a list form, so I just copy and pasted that bad boy into Excel

BUT..... as you can see above, the boxes contain different bits of info, e.g. the name and date of birth and death are in the same box. And also because the formatting was a bit different for each monarch it ended up kind of messy. I also found that much of the information that I needed was on the detail page about each Monarch:

I also tried some web scraping, but for the life of me I still haven't got this to work the way I want it to. So I went old school, and manually entered everything into an Excel spreadsheet.

That's right. Manual data entry.

And here's my first tip for anyone making a viz for the contest: Don't be afraid of manual data entry! Yes its very boring and yes it seems archaic - but sometimes its the only way that works for what you need, and really if you're watching tv and having a beer at the same time, its not that bad.

The second piece of data I decided to get was which countries they were the Kings or Queens of. This was painful. I put this in a secondary data source (see more below in the section about maps).

You will also see that I grabbed a picture URL from Wikipedia for each monarch. One of the things I love about Wikipedia lists is that thanks to those people who created them, there are often pictures there of exactly what you need, and they have one great quality - they can be resized!

How to resize a picture from wikipedia:

You need to do this if you want your pictures to all be the same size, and because images in the Tableau browser window do not resize once they are up on Server/Public.

A Wikipedia picture URL typically looks like this if you copy it from within the page:

http://upload.wikimedia.org/wikipedia/commons/thumb/7/77/Eadred_-_MS_Royal_14_B_VI.jpg/220px-Eadred_-_MS_Royal_14_B_VI.jpg

See that bit in bold and italics? You can change that. I changed all mine to 180px

http://upload.wikimedia.org/wikipedia/commons/thumb/7/77/Eadred_-_MS_Royal_14_B_VI.jpg/180px-Eadred_-_MS_Royal_14_B_VI.jpg


And now, although the pictures might be different shapes, they are all at least the same width.


Mock-ups

I don't normally create mock-ups for my vizzes, I usually just dive straight in, bit since I was working with Dan I first produce a 'data only' version of the viz, which looked like this:

(but without the background on the scatter plot, that came later)

I sent it to Dan and he came back with this which he mocked up:

which was starting to look pretty good. So we developed it from there. But here's where the compromises started coming in.

Backgrounds

Transparent backgrounds are not available for Tableau sheets - but we really wanted to use the distressed paper scroll look. Background images can be used, but only it seems with scatter plots, and so I had to abandon the Gantt chart (which I liked) to a scatter plot that looked something like a Gantt chart. I did this by placing the order of the monarchs in reverse (i.e. negative order) on the rows. And I couldn't figure out a way to get properly starting and ending Gantt bars, so I switched to crowns.

Dan gave me a big jpeg file with all the illustration on it and I used this as the background map.


Now the actual scatter plot on the viz I used a plain background image for because it was possible, but the bar charts I had to leave the background white. So I wrapped them all in transparent .png files of picture frames so that the borders would not be as visible or noticeable.

And then I added lots of dashboard actions. Again, a tip for folks doing a wikipedia viz - because of the nature of the data sets they lend well to exploratory vizes which are controlled by dashboard actions. And now that Tableau 9 is in play, tooltips and action responsiveness is much improved so I recommend making all actions driven from Hover.


Dual Axis Maps

Lastly, I wanted to create a map that kept England, Scotland, Wales and Northern Ireland separate, but include other countries. The default geocoding in Tableau has the United Kingdom as a whole, and England, Scotland etc... as states. So I decided to use a dual axis map to get around this and place 'State' on one axis, and 'Country' on the other and blended a secondary data source that looked like this:

Well I hope that was useful and if you are entering the contest - good luck :-)

Dieu et mon droit - Monarchy in the UK

Well its been a while, but here's a new viz showing the Kings and Queens of England.

This one was a labour of love and was made with help from my friend and pinball team captain Dan Miller who did the illustration and came up with the overall look and feel. You can see more of Dan's work here http://toothpicksandgum.com/ and here http://instagram.com/manmiller and follow him on twitter @metropolus.

Learn About Tableau

One thing that I would have liked while making this viz is transparent backgrounds for sheets.

Oh and please note that the data collection took bloody ages, so if you spot any errors please let me know. And the countries are the modern equivalents - identifying individual US states under different monarchs got a bit much to deal with.

One of the things Tableau is.....

A few days ago Paul Banoub posted this on Twitter:

and yesterday Dan Murray of Interworks posted this blog entry describing his thoughts on what Tableau is and what Tableau isn't. And I agree with everything Dan wrote (he is a smart man after all!).

However there was one thing missing from Dan's description of what Tableau is and it got me thinking that I need to blog about it.

One of the things Tableau is is the best tool yet created for data exploration

At this point you might be thinking "no shit Sherlock" but I think this is something I need to write about, so first a little history of my journey with Tableau.....

I first came across Tableau in 2010 when working at Barclaycard in the customer insight team. A lot of my job revolved around extracting information about our customers from transactional databases, finding the interesting nuggets in the data and basically turning that data into stories to provide 'insight' for use in product development, strategy and marketing decisions. In practical terms what that meant was writing code in SQL or in SAS, exporting aggregations of data to Excel to produce charts and then converting these to PowerPoints. 

The thing is that this process is not particularly forgiving when there is an error in the data, or when the data story you were looking into turned out to be not very interesting or insightful. Starting the whole process again was a time consuming effort and on the fly analysis, while possible, was sometimes painful.

When I first started using Tableau, thanks to an introduction from my then new colleague Brian O'Connor, I actually had the 'personal' version which did not allow direct connection to databases. And so I was using Tableau only against Excel files. It made my life easier even then, but I was mostly using it as simply a way to make charts a lot prettier than they were coming out of Excel.

And then Brian and I had our Eureka moment. We attended a Tableau meet-up in London for a preview of version 6.0 and saw what the then small but enthusiastic group of users (including one Tom Brown) were doing with it and we realised we had only scratched the surface.

So after that my job and career took a dramatic turn for the better. I was plugging Tableau directly into Teradata, analyising data on the fly, finding outliers, spotting possible data errors, seeing patterns  and relationships and testing out scenarios at 100 times the speed I had before. I started being able to turn around answers to questions in seconds rather than minutes and began doing analysis sat side by side with my colleagues from different business teams, working together to find the stories in the data before shipping off the results to PowerPoint. 

And for a long time that's the only way I used Tableau. I am very happy to admit that I had never even heard of the words Business Intelligence, had no background in IT and had no concept of things like Cognos and Business Objects. I did not produce dashboards, or manage servers, or consider how other people would use Tableau, I was using it for my own needs.

That is what I mean by 'data exploration'. Its the process of plugging directly into some data and experimenting until you find an answer to a question you may have never known existed. I think its the most important part of using Tableau (and its the reason why I still do not plan out a dashboard before I play with and understand the distribution and relationships of the data).

And that's why I'm writing this blog post. Because when I look at everything I've done so far on this blog, its mostly been in the context of using Tableau to produce nice looking and user friendly dashboards for other people to consume. But if you took all that away, if took away Tableau Server, Tableau Public, Tableau Online, took away Story Points and even just the ability to produce dashboards in Tableau desktop - it would still be my favourite piece of software ever produced. 

PS - have a nosey around here for some interesting background on the development of Tableau

Guest Post! A look at the success of the UCONN basketball team over the years

I've  been a bit distracted from blogging recently so new posts haven't exactly been coming thick and fast. BUT you are in luck, because my colleague Chamberlaine Kerr has come up with a cool basketball related viz and she's chosen this as the place to debut it.

Chamberlaine also works for Slalom Consulting and is helping to drive growth of the data visualization practice at our Hartford office. This is Chamberlaine's first foray into the world of Tableau Public and I think its a good one. You can find her on twitter as @ChamberlaineK

Chamberlaine Kerr

Slalom Consulting – Business Intelligence

Hartford, Conn.

In February, 2012 I started my career with Slalom Consulting at our headquarters in Seattle. After roughly one-and-a-half years I relocated to Hartford, Conn., and joined Slalom’s Information Management and Analytics practice.

Prior to Slalom I attended the Foster School of Business at the University of Washington – go Dawgs!   After moving to Connecticut, I quickly realized we aren’t the only Huskies around.  I now refer to my alma mater as the Huskies of the Best (oops! I mean West*) coast.

I’d like to say a huge “thank you” to my Slalom Consulting colleagues Peter Gilks (for allowing me to take over his blog for the day) and Curtis Looney (for helping with the original POC).  Hopefully my own blog will be a part of the not-so-distant future.   In the interim, I want to share the first Tableau viz I created outside of client work – a UCONN Men’s Basketball viz!

The Viz

This past year the UCONN Men’s Basketball team took #Winning to a whole new level as they laughed all the way to the NCAA championship.  The 2013-14 season was UCONN’s 4th NCAA Championship win in the last 16 years … not a bad start for Kevin Ollie’s first year as head coach.
With this year’s college basketball season well underway, it’s a good time to take a deeper look at some of the UCONN Husky’s historical trends.
Please feel free to comment.  All feedback is welcome and much appreciated.  Enjoy!

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Skyscrapers in New York update

A year a go I made this blog post for Tableau Public Design Month, including a viz on the tallest buildings in New York.

Well over the last year a new very tall building has popped up in the city to take the number 2 spot away from the mighty Empire State Building and so I thought it was time for an update.

The new building is 432 Park Avenue, the tallest residential building in the Western Hemisphere. Its penthouse apartment is currently for sale listed at $95m.

432 Park Ave is part of a new craze for super skinny super tall luxury residential buildings in New York, many more of which are in the pipeline. I'm not really a fan of these new buildings, especially since many of the apartments will be bought and left empty. But whatever happens, I'll try to keep this viz up to date.

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A Rough Guide to Tableau Dashboard Actions

As you probably can tell by now, I really enjoying building data visualisations in Tableau. Whether for this blog or for work, I strive to build dashboards that people will be able to use to explore the data at their own pace and discover their own insights.

One way I attempt to do this is by using, what I hope is, engaging visual design. The other is by building in interactive features into the dashboard that people can play with to start changing the views of the data. This is accomplished in three primary ways: Quick Filters, Parameters and Dashboard Actions. Of these three Dashboard Actions have become my favourite as they are probably the most flexible and offer the most immersive experience. So here's my rough guide to Tableau Dashboard Actions. Its not completely exhaustive, and its not particularly technical,  but if you are fairly new to Tableau, or even an experienced user, I hope you will find it a useful guide.

What is a Dashboard Action?

A dashboard action is an interactive element on a Tableau dashboard that is driven from the worksheets within that dashboard. There are three types of dashboard action:
 - Filter
 - Highlight
 - URL

Tableau themselves provide a good run down of how to build in Dashboard Actions here http://onlinehelp.tableausoftware.com/current/pro/online/mac/en-us/actions.html. So rather than repeat what Tableau have already documented, I am going to show a variety of use cases for using Dashboard Actions and how to implement them. Those use cases are:

Use Case 1: Basic Chart to Chart Filtering
Use Case 2: Pre-Filtering a Large Table
Use Case 3: Creating a 'Cross-Blend' Filter
Use Case 4: Showing Images
Use Case 5: Dynamic Text or Titles
Use Case 6: Linking Out to Web Pages
Use Case 7: Highlighting and Labelling
Use Case 8: Switching Dashboards
Use Case 9: Mixing Things Up