Visualize This: How to Tell Stories with Data. By Maria Popova How to turn numbers into stories, or what pattern-recognition has to do with the evolution of journalism. Data visualization is a frequent fixation around here and, just recently, we looked at 7 essential books that explore the discipline’s capacity for creative storytelling. Today, a highly anticipated new book joins their ranks — Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, penned by Nathan Yau of the fantastic FlowingData blog. (Which also makes this a fine addition to our running list of blog-turned-book success stories.)
Yu offers a practical guide to creating data graphics that mean something, that captivate and illuminate and tell stories of what matters — a pinnacle of the discipline’s sensemaking potential in a world of ever-increasing information overload. For a historical perspective on infographics, be sure to see the story of Otto Neurath’s Isotype. Donating = Loving Brain Pickings has a free weekly newsletter. Share on Tumblr. Wonga, Lenddo, Lendup: Big data and social-networking banking. Photo by Johannes Simon/Getty Images The buzzword tsunami that is “big data"—a handy way of describing our vastly improved ability to collect and analyze humongous data sets—has dwarfed “frictionless sharing” and “cloud computing” combined. As befits Silicon Valley, “big data” is mostly big hype, but there is one possibility with genuine potential: that it might one day bring loans—and credit histories—to millions of people who currently lack access to them.
But what price, in terms of privacy and free will (not to mention the exorbitant interest rates), will these new borrowers have to pay? In the not so distant past, the lack of good and reliable data about applicants with no credit history left banks little choice but to lump them together as high-risk bets. As a result, they either were offered loans at prohibitively high rates or had their applications rejected. Thanks to the proliferation of social media and smart devices, Silicon Valley is awash with data. Similarly, the U.S. Top Five Big Data Trends For 2013. I can say this with absolute certainty: The holiday season will underscore the impact of big data on retail.
Already, the early sales results begin to tell the story, pointing towards data-rich e-commerce as the big winner. From comScore: Black Friday alone saw $1.042 billion in online sales. That’s the first time online spending on the day after Thanksgiving has crested $1 billion, and it’s also a respectable 26 percent increase versus Black Friday 2011. Even Thanksgiving Day, which is usually a lighter day for online spending, came in at $633 million, a solid 32 percent increase over last year.From NRF: The average consumer spent $172.42 online over Black Friday weekend.
That’s about 41 percent of their total weekend spending, up from about 38 percent last year. Meanwhile, in-store sales appeared to be mostly flat. Of course, now the question at the top of the agenda is this: Where will we go from here? Looking ahead, here are the big data trends I’m expecting in the New Year: Meet the Data Brains Behind the Rise of Facebook | Wired Enterprise.
Facebook’s Jay Parikh. Photo: Ariel Zambelich/Wired Jay Parikh sits at a desk inside Building 16 at Facebook’s headquarters in Menlo Park, California, and his administrative assistant, Genie Samuel, sits next to him. Every so often, Parikh will hear her giggle, and that means she just tagged him in some sort of semi-embarrassing photo uploaded to, yes, Facebook.
Typically, her giggle is immediately followed by a notification on his Facebook page. If it’s not, he has some work to do. Parikh is Facebook’s vice president of infrastructure engineering. The trouble is that the Facebook infrastructure now spans four data centers in four separate parts of the world, tens of thousands of computer servers, and more software tools than you could list without taking a deep breath in the middle of it all. But that’s why Parikh and his team build tools like Scuba. But it also spans a team of top engineers who deal in data — an increasingly important part of modern online operations. The Philosophy of Data.