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Stephen Baker
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The Numerati Copertina flessibile – 9 settembre 2009

Edizione Inglese di Stephen Baker (Autore)
4,2 su 5 stelle 67
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Every day we produce loads of data about ourselves simply by living in the modern world: we click web pages, shop with credit cards, and make cell phone calls. Companies like Yahoo! and Google are harvesting an average of 2,500 details about each of us every month. Who is looking at this data and what are they doing with it? Journalist Stephen Baker explores these questions and provides us with a fascinating guide to the world we're entering?and to the people controlling that world. The Numerati have infiltrated every realm of human affairs, profiling us as workers, shoppers, voters, potential terrorists?and lovers. The implications are vast. Privacy evaporates. Our bosses can monitor our every move. Retailers can better tempt us to make impulse buys. But the Numerati can also work on our behalf, diagnosing an illness before we're aware of the symptoms, or even helping us find our soul mate. Entertaining and enlightening, The Numerati shows how a powerful new endeavor?the mathematical modeling of humanity?will transform every aspect of our lives.
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  1. Lunghezza stampa
    244 pagine
  2. Lingua
    Inglese
  3. Data di pubblicazione
    9 settembre 2009
  4. Dimensioni
    13.34 x 1.65 x 20.32 cm
  5. ISBN-10
    0547247931
  6. ISBN-13
    978-0547247939
  7. Visualizza tutti i dettagli
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Descrizione prodotto

L'autore

Stephen Baker has written for BusinessWeek for over twenty years, covering Mexico and Latin America, European technology, and a host of other topics, including blogs, math, and outsourcing. He has also written for the Los Angeles Times,the Boston Globe, and the Wall Street Journal and is the co-author of Blogspotting.net.

Dettagli prodotto

  • Editore ‏ : ‎ Mariner Books; Reprint edizione (9 settembre 2009)
  • Lingua ‏ : ‎ Inglese
  • Copertina flessibile ‏ : ‎ 244 pagine
  • ISBN-10 ‏ : ‎ 0547247931
  • ISBN-13 ‏ : ‎ 978-0547247939
  • Peso articolo ‏ : ‎ 213 g
  • Dimensioni ‏ : ‎ 13.34 x 1.65 x 20.32 cm
  • Recensioni dei clienti:
    4,2 su 5 stelle 67

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4,2 su 5 stelle
4,2 su 5
67 valutazioni globali

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Daniel MacKenzie
5,0 su 5 stelle Five Stars
Recensito in Canada il 11 aprile 2015
Acquisto verificato
Great thank you
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Keith McCormick
5,0 su 5 stelle Finally. The best `water cooler talk' book thus far about Data Mining
Recensito negli Stati Uniti il 21 settembre 2010
Acquisto verificato
I am a Data Miner and a Data Mining software trainer. I really enjoyed this book. My audience is not made of full time data miners (usually), but rather data analysts who are new to data mining. They are not experts who develop their own technologies, but rather are purchasers of software who use the software to Mine data with the most established of the techniques. They report to managers, and have co-workers, that are also new to data mining, curious about what it is, anxious to clarify its definition, wondering about possible application areas, working to effect the bottom line.

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.
17 persone l'hanno trovato utile
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Neil Lewis
5,0 su 5 stelle Targeting customers through their data trails
Recensito nel Regno Unito il 19 settembre 2008
Acquisto verificato
Companies, political parties, advertisers and individuals are harnessing the masses of data in our increasingly digitised world to know more about us than ever before. Businesses like Amazon and Google sift through our every click (and solicit our feedback) to find out more about us so they can customise what they sell us, both to keep us happy as customers and to increase their profits. Supermarkets use loyalty schemes to pinpoint their sales promotions to good prospects in increasingly elaborate ways. Political parties know who the floating voters are and what messages will make them vote for their policies. How do they do it, and what are the implications for our privacy? There are few technical details here, but this is a good introduction to the world of data mining.
7 persone l'hanno trovato utile
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Sandro Saitta
4,0 su 5 stelle An interesting journey in the data mining world
Recensito negli Stati Uniti il 11 novembre 2010
Acquisto verificato
Whether you are a shopper, a voter or a blogger, you will find a chapter in The Numerati that will be of interest to you. Stephen Baker has done an excellent job in explaining what companies can do with their data. For getting knowledge from these data, companies use mathematicians and computer scientists (what Baker calls the numerati).

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."
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David Bradshaw
3,0 su 5 stelle Disappointing
Recensito nel Regno Unito il 8 marzo 2009
Acquisto verificato
This is well written journalism that concentrates on the numerati themselves. Nothing wrong with journalism per se (I was a journalist myself for some years), but there's a bigger story to be written about than this. I was hoping for a more insightful analysis of the techniques, implications and/or limitations of mathematical and statistical analysis being applied at massive scale on the world around us. But what the author delivered was a set of interesting anecdotes.
3 persone l'hanno trovato utile
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