The biggest beneficiaries of big data would seem to be retail giants, like Amazon and Walmart. But according to a 2012 study by Gartner, the hottest industries for big data are banking, communications, government, and manufacturing. For details, check out this insightful (but ugly) infographic created with Tableau.
It was just a matter of time until someone realized that Facebook is a treasure trove of psycho-social data. When people are active on Facebook, liking this and that, it can create a pretty interesting picture of a person’s personality. With each press of the Like button, I’m aware that I’m contributing to a highly revealing database of my predilections – my political leanings, my consumer interests, and what kind of news stories grab my attention.
WolframAlpha was one of the first to offer a social analytics tool for regular folk to mine their own data, but it mostly provides summary statistics. Now, real scientists from the University of Cambridge have uncovered deeper and more meaningful conclusions from a person’s Likes. I was pretty surprised at how accurate their tool was for me. Try it out for yourself.
Last week’s map visualizations wowed me, but today’s Infographic of the Day from Fast Company blew my mind. Basically, what the project’s author, Santiago Cruz, did was create an interactive map of relationships between Twitter employees based on their public tweets. This massive and incredible work of data art wasn’t paid for and is merely Cruz’s sample work for his visualization freelancing business.
Big data might be losing some of its luster, but the invariable truth is that data continues to grow. According to IBM, 90% of the data today has been created just in the last two years. As long as we use computers, data will grow.
For the true believers, one of my favorite blogs, Data Science 101, posted these five highlights from the first issue of the journal Big Data. You know what I’ll be reading the next couple of days whilst on my porcelain throne.
Ok, I misspoke, in a way. The U.S. economy, as seen by large corporations and financial institutions, is growing at an exponential rate, thanks to “increased productivity“. That same $15 trillion-dollar economy, from the eyes of the millions of unemployed, is shrinking to a distant memory – a time when they could afford groceries without food stamps, a time when they could afford to take vacations.
Reports from the labor department and employment firms like ADP show that new jobs are being created, but as the blog Calculated Risk points out, it’s not enough. Actually, far from it. Accounting for population growth, we need millions more new jobs.
You would think that based on my posts that the world of serious data visualization (which excludes cutesy infographics) is all about mapping metadata. Here’s yet another example that this might really be the trend: Like the Average Commute Times project, Rich Blocks, Poor Blocks uses public data from the U.S. Census American Community Survey to map median household incomes per census tract. Thanks to this simple tool, it’ll be a lot easier to convince my wife to get a job when she sees that we make less than our neighbors.
A glance alone at this data visualization project is enough to elicit a jaw-dropping “wow”. Based on public data from the 2006-2011 U.S. Census American Community Survey, the interactive map gives you average commute times for every zip code in the United States. My home, the greater Los Angeles area, is bad, of course, but less urban centers in the Midwest, like northeast Arizona and northwest New Mexico, have average commute times of up to an hour!