Small book review: Super Crunchers

As written in an earlier post, Super Crunchers is a new book about data mining by Ian Ayres. Super crunching, according to Ayres is the action of applying data mining algorithms to real situations in order to make better decisions from data. I will make it clear right now: Super Crunchers will not give you examples of complex data mining techniques in real situations. Most of the book shows the use of randomized experiments (there are also a few pages on neural network, but that’s all).

This book is nevertheless a very interesting reading for many reasons. First, the author did a very good job in introducing the basic ideas behind data mining for non-specialist readers. In addition, Ayres has collected a bunch of small, and very interesting, stories about people crunching data (wine quality prediction, baseball, etc.). In every situations, the author shows how crunching numbers help people make decisions but also how difficult it is to make non-expert believe in your results. This is, to my opinion, the most interesting aspect of the book.

Super Crunchers is very well written (I’m realizing now that I write that for most of my book reviews, but believe me you’ll enjoy reading this book). After giving some examples, Ayres describes the actors of this industry (super crunching). He then introduces the idea of randomized experiments. There is also a nice chapter about the confrontation “Experts Versus Equations”. He concludes by explaining why this enthusiasm for super crunching is happening only now and not before.

Finally, although the action of super crunching is certainly more about applying statistic methods (rather than data mining) to real situations, this is a must-have book, even for specialists in data mining. For interested reader, an interview of Ian Ayres is accessible here.

Ayres, I., Super Crunchers, Why Thinking-by-Numbers Is the New Way to be Smart, Bantam Books, 2007, 260p.


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Comments Icon4 comments found on “Small book review: Super Crunchers

  1. While I liked Super Crunchers somewhat (review here), I did not find it as useful as Competing on Analytics (review here). Ian writes well but his refusal to call data mining and data miners by their correct name was irritating and he waved his hands a little too often for me – making assertions and not drilling down.
    Anyway, worth reading both books I think

    James Taylor
    Author, with Neil Raden, of Smart (enough) Systems

  2. Thanks for mentioning “Competing on Analytics”, I didn’t know the book. I agree with you on the issue of using “super crunchers” instead of “data miners”. However, since this book is more about vulgarizing the field, I find it alright.

    Ayres states that super crunching is not as easy as data mining, since it concerns decision support on real-life data. This is were I disagree with him (about the definition of what data mining really is).

  3. Thanks for pointing out “Competing on Analytics”. I just ordered the book. I did, however, very much enjoy Ayres’ book. He seems to focus exclusively on regression as a his tool of choice and provides little details indeed about the various applications he mentions. However, he does a very nice job, I think, at making things accessible to a broad audience and several of the examples are rather compelling as they clearly show how data mining (super crunching, or whatever you wish to call our science) often challenges conventional “wisdom”. I am rather certain that Ayres did not write the book for experts but rather for lay people. As such, I think the book is a success, and should certainly help people better appreciate our science and what it can offer. We can always argue about the choice of names, and some of the assertions that Ian does indeed make (and that we could easily take up issue on), but again, overall, I think the book is a welcome boost to data mining in general. I am eager to see what additional light “Competing on Analytics” sheds on our fascinating science. By the way, James, thanks for your review of it, that you pointed to in your comment.
    Christophe (

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