- Paperback: 256 pages
- Publisher: Mariner Books; Reprint edition (September 9, 2009)
- Language: English
- ISBN-10: 0547247931
- ISBN-13: 978-0547247939
- Product Dimensions: 5.2 x 0.6 x 8 inches
- Shipping Weight: 12.8 ounces (View shipping rates and policies)
- Average Customer Review: 72 customer reviews
- Amazon Best Sellers Rank: #1,349,422 in Books (See Top 100 in Books)
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The Numerati Paperback – September 9, 2009
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"[A] bracing behind-the-screen investigation into the booming world of data mining and analysis . . . fascinating." Booklist, ALA, Starred Review
"Highly recommended for general readers with an appreciation for contemporary cultural phenomenons." Library Journal
"An eye-opening read for even the techiest among us." Bookpage
"Deserve[s] a spot on your shelf." Steve Rubel, AdAge
"A well-considered take on a hard-to-grasp subject." Kirkus Reviews
"Stephen Baker could have easily gone for spooky in this depiction of the Numerati . . . but Baker's deep reportage goes beyond smart shopping carts that entice us to run up our grocery bills and political messages crafted on our preference for Chianti . . . The Numerati, Baker writes, try to model 'something almost hopelessly complex: human life and behavior.' They're making progress."
"'The Numerati' is a book about math that won’t cause liberal-arts majors to heave it across the room. The slender volume contains not a single esoteric Greek letter or mystifying equation. What’s more, writer Stephen Baker artfully conjures up vivid images to explain what he’s talking about and why a reader should care." Christian Science Monitor
"Utterly fascinating . . . Baker, a veteran journalist at BusinessWeek, manages to explain this cutting edge phenomenon and its sometimes-frightening impacts in accessible prose . . . Baker also does not shy from potential problems with all this data mining and analysis . . . Baker's accessible prose and analysis illuminate this startling new world and its potential problems." Seattle Post-Intelligencer
"'The Numerati' is a kind of travelogue, a report from the shadowy regions where data mining, the search for new algorithms and the divination for the hidden meanings disclosed by our choices animates a type of research that was impossible to imagine before the computer . . . an interesting book . . . Baker knows well that the Numerati cannot answer the big questions, like where do we go from here? But perhaps they can help us avoid falling off whatever cliffs we decide to peer over." The Oregonian
"Crisp, well-reported ... Baker writes with smooth and accessible assurance." - San Francisco Chronicle
"An eye-opening and chilling book." - Portfolio
"Baker singles out the danger to privacy the Numerati and their techniques represent, but he doesn't take sides. He also points out the advantage of Amazon knowing what books you want, or an insurance company offering discounts to drivers who install electronic monitoring equipment in their cars . . . still, he paints a pretty scary picture." - Chicago Sun-Times
"Deserve[s] a spot on your shelf . . . Baker details how companies are hiring math geeks to dissect and make sense of mountains of data to spot everything from consumer patterns to future terrorists." -- Steve Rubel, AdAge
"'The Numerati' is fascinating and a bit frightening -- a well-written consideration of why you might want to drive a different way to work every now and then, or buy ginger ale rather than Coke, just to throw 'them' off a little." -- Utah Daily Herald
About the Author
STEPHEN BAKER was BusinessWeek's senior technology writer for a decade, based first in Paris and later New York. He has also written for the Los Angeles Times, Boston Globe, and the Wall Street Journal. Roger Lowenstein called his first book, The Numerati, "an eye-opening and chilling book." Baker blogs at finaljeopardy.net.
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I disagree with those reviewers that suggest that Baker does not understand the methods. He tries very hard at explaining them to a general audience. I have tried to do the same, and he does an admirable job. I would be less than candid, if I didn't admit that I winced once or twice. But it is tough to strike the right balance.
I think he has does a brilliant job at choosing a structure of his book. His chapters are not structured to be on the different methods. One negative review claims that he `mentions' Support Vector Machines, but never mentions cluster analysis. It is simply not true. The "Voters" chapter is dedicated almost in its entirely to cluster analysis and market segmentation. I have taught this topic to thousands of software users, and I think it is a great chapter. He avoids technical jargon including the names of the methods because he audience is not me. His audience is everyone who does not do data mining, but is potentially effected by it, curious about it. So, if you want a chapter on how Support Vector Machines work, one can barely imagine a less appropriate choice. If you want a gentle introduction to many techniques like Neural Nets and Classification Trees go with Berry and Linoff's Data Mining Techniques. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management For an advanced discussion, many of the negative reviews have additional suggestions. I give LaRose's trilogy mixed reviews, but you can consider them. Discovering Knowledge in Data: An Introduction to Data Mining is the first.
Instead, and wisely, he structures his book as a handful of chapters on application areas. Each chapter involves interviews with experts, the Numerati of the title. There is usually one primary lead character in each chapter. Does he `gush'? Is he informal? A little perhaps, perhaps more than I would have liked. I like my Data Mining books technical, succinct, algorithm based, and cooly academic in style. But does a general audience want that? I like my astronomy books to be gentle on me. I like my physics books to be gentle on me. Why wouldn't a non-data miner want a gentle introduction?
As one critic noted, he does "insert himself into the narrative". He chats about the room in which he is interviewing. He mentioned Starbucks, and the physical description of his subjects. Some would leave that to Dickens and leave it out of this book. I might have cut back on that a bit, but incompetent? No. Not by a long shot. This is a great non-technical introduction to an important societal trend. I actually learned a fair amount. For instance, the concept of `next friend' and its use in social networks was new to me. I have also ranked this book higher than "Supercrunchers". Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart I believe the author of that book, while a fine analyst, just doesn't get it when it comes to Data Mining and where it is taking us. Davenport's book Competing on Analytics: The New Science of Winning, reads too much like Harvard Business Review for a general audience, and it's kinda dry. Baker's book, in contrast, nails it. I recognized my future in his book. Read it, and you will understand what Data Mining is attempting to do, and the challenges it faces.
Baker takes us in a journey divided in seven parts (chapters). Each of this parts explain the possible application of data mining in a specific area. The journey is passionate and thus very interesting to read. The main point of his book is the ability of companies to build our behavior by mining personal data in various domains. As he explains, this would be impractical manually:
"This means that marketers must scope us out as individuals. One approach would be to deploy battalions of psychology [...] That's impractical."
The main question for companies that collect data about us is what do we do, that might predict what we will do next? The book gives answers with practical examples.
By the way, Baker makes a very good vulgarization of decision trees on page 88. The author also makes a good point about data mining by stating that the aim is not to be perfect, but to do better:
"Truth is not a make-or-brake test for the Numerati. They triumph if they come up with better, quicker or cheaper answers than the status quo."
To conclude, this is a very good book that any data miner should read to get a tour of possible applications. Maybe Baker goes a bit too far on what data mining can do (spy you) and this may frighten people:
"In the age we're entering, our lives will be described, studied, and predicted, every day more, through this statistical analysis."
Then this book is (most probably) a piece of relief for you, as it has been for myself. For several years I am part of different bodies and institutions that try to draw conclusion from their customer historical track records. After several years of working in this trade we all come to stage, where you do not have enough source of inspiration from peers (because you left them far behind) in your industry or you already have tried most of what makes just a bit of the sense.
Stephen Baker took the time to collect the best practice and inspiration from wide array of industries and environments on how data can be systematically turned into more business or power within your battlefield. Even though some of the concepts are not easily transfarable into my industry, I still was amazed and inspired by way they were approaching their data hurdles. It is very thought provoking how far we already reach in datamining - and top of that - utilizing the results of it. I launched several projects within my company to tranfer the principles discussed in this book.
If you still are unsure about buying this book, then invest few dollars of its price at least into understanding how much digital traces and hints you leave around and how much more privacy invading is just around the corner for next years.
Eric Siegel, Ph.D.
Founder, Predictive Analytics World
Author, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die