How Companies Use Big Data to Cultivate a Brand (video)

How Companies Can Use Big Data to Cultivate a Brand: Video - Bloomberg:
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Starcom MediaVest Group's Jeffrey Seah discusses how to attract and cultivate a brand with Zeb Eckert on Bloomberg Television's "On The Move Asia." (Source: Bloomberg May 30)

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The Right To Be Forgotten, What Does It Really Mean?

The Right To Be Forgotten – What Does It Really Mean? | Dorsey & Whitney LLP - JDSupra:




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The Limits of Big Data

Pentland’s idea of a “data-driven society” is problematic. It would encourage us to optimize the status quo rather than challenge it

The Limits of Big Data: A Review of Social Physics by Alex Pentland | MIT Technology Review: "Tapping into big data, researchers and planners are building mathematical models of personal and civic behavior. But the models may hide rather than reveal the deepest sources of social ills." (read more at link above)

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Big Data, Thin Data, Thick Data, the Real World

A piece of fabric with stars and stripes in three colors is thin data. An American Flag blowing proudly in the wind is thick data. 

Your Big Data Is Worthless if You Don’t Bring It Into the Real World | Opinion | WIRED: "To really understand people, we must also understand the aspects of our experience — what anthropologists refer to as thick data. Thick data captures not just facts but the context of facts. Eighty-six percent of households in America drink more than six quarts of milk per week, for example, but why do they drink milk? And what is it like?...Rather than seeking to understand us simply based on what we do as in the case of big data, thick data seeks to understand us in terms of how we relate to the many different worlds we inhabit. Only by understanding our worlds can anyone really understand “the world” as a whole, which is precisely what companies like Google and Facebook say they want to do."

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Big Data, Big Mistake?

Big data: are we making a big mistake? - FT.com: "Cheerleaders for big data have made four exciting claims, each one reflected in the success of Google Flu Trends: that data analysis produces uncannily accurate results; that every single data point can be captured, making old statistical sampling techniques obsolete; that it is passé to fret about what causes what, because statistical correlation tells us what we need to know; and that scientific or statistical models aren’t needed because, to quote “The End of Theory”, a provocative essay published in Wired in 2008, “with enough data, the numbers speak for themselves”. Unfortunately, these four articles of faith are at best optimistic oversimplifications. At worst, according to David Spiegelhalter, Winton Professor of the Public Understanding of Risk at Cambridge university, they can be “complete bollocks. Absolute nonsense.”
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