Titanic Data Analysis - Did Passengers Get Their Money's Worth?

You may have read about the City of Charlotte's "Business Analysis Olympiad" where 12 teams of analysts from across the city departments competed in an analytical showdown. It was quite the event and Jock Mackinlay's blog post gives all the details. Data Administration Specialist Doris Phillips had the original idea to hold the Business Analysis Olympiad. And it was James Raper, Manager of Data Administration, who made the most of the suggestion and orchestrated the event.

Several weeks ago well before the Olympiad, Doris took the first crack at analyzing data about Titanic passengers. She shared her visual analysis with both the Oracle Developer Tools Users Group (ODTUG) and with us at Tableau. And were we knocked out by her work. Titanic buffs will of course enjoy this (there are a lot of people who study the Titanic story - and I don't mean the movie). But even if you don't have much of an interest in the fate of the Titanic, you'll still be fascinated by her visualization work.

City of Charlotte Wows Us with Innovative "Business Analysis Olympiad"

I just returned from one of the most interesting and innovative business events I've ever attended. The City of Charlotte sponsored a "Business Analysis Olympiad" to promote the business value of visual analysis as well as to create a community of visual analysts within the city’s key businesses. When employees use data and information more effectively, they make better business decisions and thus serve the citizens of Charlotte better.

The contest was created by the Business Systems Support group in the IT department and attracted teams from across the city’s 14 departments to learn about the new ways that they could visualize and analyze data. In other words, IT functioned as a pro-active consultant to business units to improve their present practices.

State Electoral Votes over Time

Robert Kosara has an interesting post up on EagerEyes where he uses Tableau to visually highlight trends in states' presidential party preference. Two readers suggested that the states should not be arranged alphabetically, instead clustering them in some fashion that groups like-minded states.

Showing Electoral College Impact With Overlapped Bars

Robert Kosara has created an overlapped bar chart that describes the history of US Presidential votes, which is discussed in his EagerEyes blog. This view is interesting because the bars for the percent Electoral vote is on the top when it is less than the percent of Popular vote and on the bottom when it is greater. Although he used Excel computations to generate the view, it is easy to generate in Tableau by defining an extra column. Playing with the resulting workbook, I found that it is effective to sort the bars by the percent of the popular vote because you can clearly see all the presidents that were helped by the Electoral college to get above 50%.

More can be simpler when telling data stories

The Junk Charts blog had a posting about the importance of making a data view “as simple as possible but no simpler”, which used a great example from Professor Gelman’s recent book “Red State, Blue State, Rich State, Poor State”. His scatter view does clearly show the interaction of social and economic views. It is also relatively easy to see the social clustering. However, it is harder to see the economic cluster. I think you can add more to Gelman's data view to tell his story more effectively.

Do You Say Coke, Soda or Pop? A Map Visualization Shows Your Likely Answer

A good Tableau customer, Michael Cristiani of Market Intelligence Group, recently sent us a challenge. He had discovered a dataset for which people were surveyed about their choice of words for their preferred icy, carbonated beverage. Specifically, did they use the word “coke”, “soda”, “pop” or some other word? There were nice maps on the site but with Tableau 4.0’s new mapping capabilities, he wanted to know what we could do with the data. Given that I was in a hotel room when I read about this, I decided to give it a go with Tableau 4.0 (beats renting a bad movie) and came up with some interesting results.

Sparklines - Easier Than I Thought

I recently had to look at a lot of data categories as their values moved through time. I wanted to embed these graphs in a Word document to succinctly and effectively provide visual context to my discussion points. I originally thought I would use one graph with multiple color-encoded lines but realized that it would not be very effective in my document. There were too many lines overlapping each other and you couldn't really discern what was happening for each category.

I remembered what Edward Tufte and Stephen Few recommend - sparklines - and used Tableau to create them quickly and easily.

Life Expectancy in OECD Countries

The Junk Charts blog had a posting about web publishing that included a comment by reader 'DavidS'. He suggested using quartiles in a chart about life expectancy in OECD countries. Since the data was easy to download, I explored his suggestion in Tableau. Although the original chart is a good summary of the upward trend of life expectancy, David is correct that a more statistical view showing outliers demonstrates that the variance has increased even though the range has reduced.

Can You Improve this Graph?

One of the blogs I read regularly is Flowing Data, which discusses effective visualization techniques for making sense of data.  A recurring topic is a challenge to the readers: can you improve this graph? 

EagerEyes Blog Lists Top 10 Information Visualization Influences on Tableau’s Jock Mackinlay

I love it when people much more knowledgeable than I give me inside views into what shaped them. It’s fascinating to see what influenced them as they developed into the industry experts we know. EagerEyes.org, a terrific blog with lots of resources on information visualization, recently asked Tableau’s own Dr. Jock Mackinlay to name his top 10 influences.