Data visualization is not a new topic any more. Edward Tufte launched the field onto the public stage in 1983 with the self-published book The Visual Display of Quantitative Information. This was followed with Envisioning Information in 1990 and several others. The influence of these books and and the acceptance of data visualization as an important focus in our data-intense existence was highlighted further when president Obama appointed Tufte to the American Recovery and Reinvestment Act’s Recovery Independent Advisory Panel “to provide transparency in the use of Recovery-related funds.” The continued importance of data visualization is evident in several recent articles in the New York Times this week.
It’s all Connected: An Overview of the Euro Crisis (24 Oct., 2011)
This excellent interactive visualization reduces the obtuse complexity of the European debt crisis to something we all can fathom. A single data visualization is used and presented multiple times to emphasize different aspects of the situation. This visualization is simple and compelling enough that one can imagine it being used to explain all kinds of complex trade between nations. The Times not only reports on data visualization trends but is a leader in using interactive data visualization to communicate with its readers. Bravo.
Google Announces New Data Visualization Tools for Analytics (19 Oct., 2011)
This article in the Technology section actually starts off with a picture of the Minard map of Napoleon’s March which Tufte describes as “the best statistical graphic ever drawn” (and sells as a poster). The article describes Google Analytics’ new Flow Visualization and demonstrates that the folks at Google have been reading Tufte and ‘get it’ when it comes to the power of data visualization:
Flow Visualization takes the data Google collects and then creates an interactive visual map. The graphic will illustrate the number of people who are navigating a Web site, but also the path they take on their journey: entering through the home page, clicking on interior links and viewing ads along the way. …
“We think this is going to help data be told in a story that can be understood very quickly and easily,” Ms. Wojcicki said.
It’s nice to see “storytelling” mentioned as part of the goal of data analysis. Humans have ben story tellers since the invention of language and any important data analysis or visualization needs to be communicated as part of a rich, compelling story. If you don’t know what the bigger story is, how can you possible hope to create meaning from data?
The Big Business of ‘Big Data’ (24 Oct. 2011)
Another article in the Technology section describes how big companies like Google, Amazon and Facebook are working with large datasets. By stitching together a couple of disparate sentences from the article we can create an argument for the importance of pattern recognition and simple answers as important tools in rendering all this data in a form fit for human consumption:
… data is growing enormously.
Big Data is really about, however, the benefits we will gain by cleverly sifting through it to find and exploit new patterns and relationships. …
… a common problem in the Big Data proposition: Often people won’t know exactly what hidden pattern they are looking for …
Rather than search for new patterns in the big piles of data, Domo will focus on delivering to a top executive simple existing data, like how large a bank’s deposits are on a given day, or how many employees a company has, that are still hard to locate. “Everyone is saying that the team with the best data analysts will win,” he said.
“We have all the data we need. The focus ought to be on good design, and telling the vendors the simple things you really need to see.”
Nothing is more important than “good design” and concise summaries of “the simple things you really need to see.”
More Jobs Predicted for Machines, Not People (23 Oct, 2011)
This piece reviews a new book by two economists that paints a gloomy picture of how improvements in technology and computer capabilities are allowing corporations to use technology to do the work that humans used to do. The employment picture for unskilled labor, and an increasing amount of skilled labour, the authors suggest, is dire. But the article ends with sage advice:
“This technology can do things now that only a few years ago were thought to be beyond the reach of computers,” Mr. Brynjolfsson said.
Yet computers, the authors say, tend to be narrow and literal-minded, good at assigned tasks but at a loss when a solution requires intuition and creativity — human traits. A partnership, they assert, is the path to job creation in the future.
“In medicine, law, finance, retailing, manufacturing and even scientific discovery,” they write, “the key to winning the race is not to compete against machines but to compete with machines.”
Enabling the symbiosis of narrow and literal-minded computers, the “number crunchers”, and intuitive and creative humans, the “pattern recognizers” is what good data visualization and good user interface design is all about. We couldn’t agree more that an important key to a bright future is figuring out how best to put these two incredible machines, the number cruncher and the pattern recognizer, to work together.