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What Stays in Vegas: The World of Personal Data—Lifeblood of Big Business—and the End of Privacy as We Know It... by Adam Tanner
Published in September of 2014

Dataclysm: Who We Are (When We Think No One's Looking) by Christian Rudder 
Published in September of 2014.

What do we mean when we talk about big data in higher ed?  What is the deal with putting the qualifier “big” before “data”? Was data ever small? Does talking about BIG DATA make us sound somehow more digitally clued-in?  Academics who think in platforms and ecosystems rather than only in credits and classes?  Like we would be as comfortable at a TED Talk as a Convocation, at SXSW as the ASA?

My approach to achieve Big Data academic cool standing is to try to understand big data in adjacent industries. If I can make sense of big data in the contexts of Vegas and in the world of online dating, the world of academic big data should come a bit easier. It’s a theory.

Of the two books, I would recommend the Tanner book with the excellent title of What Stays in Vegas. I’ve actually never been to Vegas, never gambled, and was an easy mark in college poker games - so I thought I was perfectly positioned to enjoy this book. Tanner spends most of the book profiling the ex Harvard Business School professor turned Caesars Entertainment CEO Gary Loveman. You got to love a Wesleyan undergrad / MIT PhD who leaves certain tenure at HBS to run a casino. There may be hope for some of us yet.  Professor Loveman (although nobody calls him that) completely remade the gaming industry moving its operations from ones based on tradition and gut feelings to ones based on data. Think Moneyball for casinos. Loveman introduced the Total Rewards program at Caesars, the most successful customer loyalty and data capturing program in the history of gambling. Through this program, Caesars has the ability to analyze every aspect of individual and group gaming behavior - and can offer just the right incentives and perks to maximize gambling.  

Is there a Total Rewards equivalent for learning?  Should there be?

Dataclysm has a great premise, but unless you are obsessed with what we can learn about human behavior from the world of online dating you may want to get your big data fix somewhere else. Dataclysm is written by one of the founders of the online dating site OkCupid.  Rudder is an engaging writer blessed with access to millions upon millions of anonymized records from the online dating site that he helped found. He can tell us what characteristics are seen as most attractive to would-be daters, broken down by age, sex, race, region, religion, political preference, and any other of a million variables. He can share with us how our online behaviors match our stated preferences, and when they do not.  He can let us know how matchmaking behaviors can be influenced by small changes in website design, or even the size of the pictures of OkCupid members displayed on the site.  

Perhaps Dataclysm would be more appealing to those readers who may one day find themselves on an online dating site. I liked learning about how the big data behind OkCupid can inform us about preferences around love and sex, I just wanted more about how online dating connects with larger trends of data collection and analysis on the Web and beyond.   

What books on big data would you recommend?

What are you reading?

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