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beets_enjoyer 's review for:
Big Data: A Revolution That Will Transform How We Live, Work, and Think
by Viktor Mayer-Schönberger
Having been on a big data/statistics binge recently, I can't help but be struck by the similarities in approach and execution between the major titles on the subject. Crack open any of these books and the authors are sure to regale you with the torrid tales of Billy Beane and his baseball Sabermetricians, Target's premature targeting of expectant mothers, and lest we forget - fawning references to the zany whizzes over at Google.
Still, the subject is so intensely fascinating that it doesn't matter much. My fascination, in no small part, comes from my belief that the big data approaches made possible by machine learning and distributed processing are a key component of where we are headed as a society. Today, algorithms can be used to translate languages (albeit it imperfect) and predict everything from crime hotspots to default rates, using data that seems almost unrelated to the matter at hand. The ingenuity and mathematical sophistication of the people who create these algorithms is awe-inspiring.
In covering them, "Big Data" does worse than most. It reads like a checklist of plane fodder tropes. Neologisms ("Algorithmists") abound, as do catchphrases ("N = All", "Big Data mindset"). The book lacks the practitioner's viewpoint of [b:The Signal and the Noise: Why So Many Predictions Fail - But Some Don't|13588394|The Signal and the Noise Why So Many Predictions Fail - But Some Don't|Nate Silver|http://d202m5krfqbpi5.cloudfront.net/books/1355058876s/13588394.jpg|19175796]. Unlike [b:Automate This: How Algorithms Came to Rule Our World|13542772|Automate This How Algorithms Came to Rule Our World|Christopher Steiner|http://d202m5krfqbpi5.cloudfront.net/books/1346165165s/13542772.jpg|19107063], it gently sidesteps the close but oh so uncomfortable issue of technological unemployment. Even more egregiously, it does this in favor of pages upon pages arguing against the distant straw man of Minority Report-style crime prediction. Throughout the book, one gets the sense that the authors and/or the editor had a vague desire of creating a manifesto for the new age of Big Data, but not the balls to go all out in the endeavour. Mashed together with the fluffy and excited tech journalism that takes up the majority of the book, the end result feels intellectually lazy and padded to the extreme.
I would not recommend this book.
Still, the subject is so intensely fascinating that it doesn't matter much. My fascination, in no small part, comes from my belief that the big data approaches made possible by machine learning and distributed processing are a key component of where we are headed as a society. Today, algorithms can be used to translate languages (albeit it imperfect) and predict everything from crime hotspots to default rates, using data that seems almost unrelated to the matter at hand. The ingenuity and mathematical sophistication of the people who create these algorithms is awe-inspiring.
In covering them, "Big Data" does worse than most. It reads like a checklist of plane fodder tropes. Neologisms ("Algorithmists") abound, as do catchphrases ("N = All", "Big Data mindset"). The book lacks the practitioner's viewpoint of [b:The Signal and the Noise: Why So Many Predictions Fail - But Some Don't|13588394|The Signal and the Noise Why So Many Predictions Fail - But Some Don't|Nate Silver|http://d202m5krfqbpi5.cloudfront.net/books/1355058876s/13588394.jpg|19175796]. Unlike [b:Automate This: How Algorithms Came to Rule Our World|13542772|Automate This How Algorithms Came to Rule Our World|Christopher Steiner|http://d202m5krfqbpi5.cloudfront.net/books/1346165165s/13542772.jpg|19107063], it gently sidesteps the close but oh so uncomfortable issue of technological unemployment. Even more egregiously, it does this in favor of pages upon pages arguing against the distant straw man of Minority Report-style crime prediction. Throughout the book, one gets the sense that the authors and/or the editor had a vague desire of creating a manifesto for the new age of Big Data, but not the balls to go all out in the endeavour. Mashed together with the fluffy and excited tech journalism that takes up the majority of the book, the end result feels intellectually lazy and padded to the extreme.
I would not recommend this book.