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. And in a culture of equally increasing infographics overload, where we are constantly bombarded with mediocre graphics that lack context and provide little actionable insight, Yau makes a special point of separating the signal from the noise and equipping you with the tools to not only create better data graphics but also be a more educated consumer and critic of the discipline. From asking the right questions to exploring data through the visual metaphors that make the most sense to seeing data in new ways and gleaning from it the stories that beg to be told, the book offers a brilliant blueprint to practical eloquence in this emerging visual language. Donating = Loving Share on Tumblr

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. 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. “It gives us this very dynamic view into how our infrastructure is doing — how our servers are doing, how our network is doing, how the different software systems are interacting,” Parikh says. In the nine years since Mark Zuckerberg launched Facebook out of his Harvard dorm room — Monday marks the anniversary of the service — it has evolved into more than just the world’s most popular social network.

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. Thanks to the proliferation of social media and smart devices, Silicon Valley is awash with data. Similarly, the U.S. Social media is just the tip of the iceberg. Those without smartphones or Twitter accounts need not despair.

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. 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: More and different use cases. Enhanced collaboration and integration. Related Resources from B2C» Free Webcast: Four Ways To Improve Your Content Marketing Maturity Better insights. Amped up mobile wars. Increased scrutiny of privacy issues. That’s a brief synopsis of the major big data trends I see on the horizon.