Seven Methods for Transforming Corporate Data Into Business Intelligence
Author: Dhar, Stein
List Price: $29.95
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ISBN: 0132820064
Publisher: Prentice Hall (06 December, 1996)
Sales Rank: 31,956
Average Customer Rating: 4.4 out of 5
Customer Reviews
Rating: 4 out of 5
Good Intro to AI and Business Application
I read this book after I read Data Mining Techniques For Marketing, Sales and Customer Support. There is a significant overlap between the books, but i suppose each one has a slightly different focus.While Data Mining Techniques focused and covered techniques most relevant for marketing purposes, Seven Methods is more general with enterprise business intelligence in mind. While rule-based systems and fuzzy logic are absent from Data Mining Techniques, Seven Methods is missing market basket and link analysis.
Although Seven Methods is also written for laypersons, you can still sense that authors are of technical background and have interesting stories to tell about details of each algorithm. On the other hand, authors of Data Mining Techiques are of consulting background or practioner of techniques rather than researcher.
I would suggest that, if you are not a core marketer, Seven Methods will better suit your appetite for learning a range of data mining techniques. If you are a marketer, then read Data Mining Techniques.
Rating: 5 out of 5
Revealing the Practical without Being Sidetracked by Gee-Wiz
In my college days, I really got into exotic/fun stuff like Fuzzy Logic, Expert Systems, and Case-Based Reasoning. I read lots of books that delved into some author's view of the subtle nuances of some technical refinement or another. I even fancied myself as knowledgeable about Genetic Algorithms and published a research paper on the topic. [Yes, I'm a really exciting guy.] Since then I've come to appreciate that none of these "fancy" methods is perfect and they all have their strengths, weaknesses and best applications. The strength/contribution of "Seven Methods..." is that it rises above the Gee-Wiz details (many of which have come and gone) and instead takes a results oriented approach that summarized where each approach would best succeed in a practical business setting. It has consistently placed in the "top ten" of data-mining reviewers' lists and I think it will continue there for years to come because of this high-level/practical perspective. Each chapter illustrates an alternative data-mining approach using simple/tangible examples. The book ends with seven nontrivial and real world case studies to further illustrate how corporations have come to apply these methods to make (or save) real money.
Rating: 1 out of 5
Do not buy this book
This book is not intended for line of business managers that want to really gain insight from data. It goes into stuff that does not really apply to business needs: brain simulation, neural networks, artificial intelligence. Also, most of the data transformation/usage examples are shallow.
jlpreza
Wien, Osterreich
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