Seven Methods for Transforming Corporate Data Into Business Intelligence [Paperback]

Vasant Dhar (Author), Roger Stein (Author)

Book Description

ISBN-10: 0132820064 | ISBN-13: 978-0132820066 | Publication Date: December 6, 1996 | Edition: 1st

Advanced techniques for transforming data into decisions. Today's knowledge-intensive decision support tools can make organizations dramatically more intelligent, by utilizing the information organizations already possess, taking advantage of today's increasingly widespread data mining and warehousing systems, and leveraging mature and powerful artificial intelligence technologies. This is the first book to cover these new approaches in depth, for both the business decision maker and the technologist. Authors Vasant Dhar and Roger Stein are leading practitioners of AI in the financial services industry. They present detailed, up-to-date coverage of all major AI techniques, including genetic algorithms, neural networks, rule-based systems, fuzzy logic, case-based systems and machine learning algorithms. They discuss advanced OLAP and data warehousing systems, and show how to select the most appropriate tool for each business challenge. The book includes detailed checklists of key organizational and technical issues to consider, several practical case studies, and a common methodology and analysis techniques.

Editorial Reviews

From the Back Cover

Today's knowledge-intensive decision support tools can make organizations dramatically more intelligent, by utilizing the information organizations already possess, taking advantage of today's increasingly widespread data mining and warehousing systems, and leveraging mature and powerful artificial intelligence technologies. This is the first book to cover these new approaches in depth, for both the business decision maker and the technologist. Authors Vasant Dhar and Roger Stein are leading practitioners of AI in the financial services industry. They present detailed, up-to-date coverage of all major AI techniques, including genetic algorithms, neural networks, rule-based systems, fuzzy logic, case-based systems and machine learning algorithms. They discuss advanced OLAP and data warehousing systems, and show how to select the most appropriate tool for each business challenge. The book includes detailed checklists of key organizational and technical issues to consider, several practical case studies, and a common methodology and analysis techniques.

Product Details

• Paperback: 269 pages
• Publisher: Prentice Hall; 1st edition (December 6, 1996)
• Language: English
• ISBN-10: 0132820064
• ISBN-13: 978-0132820066
• Product Dimensions: 9.1 x 6.9 x 1.1 inches
• Shipping Weight: 15.2 ounces
• Average Customer Review: 4.5 out of 5 stars  See all reviews (11 customer reviews)
• Amazon Best Sellers Rank: #703,136 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

25 of 25 people found the following review helpful:

4.0 out of 5 stars Two Books, Identical Content, August 15, 2000

By 

Deck P. Murray (Huntington, NY USA) - See all my reviews

This review is from: Seven Methods for Transforming Corporate Data Into Business Intelligence (Paperback)

These authors have also written a book titled "Intelligent Decision Support Methods". The two books ("Seven Methods" and "Intelligent Decision Support") are virtually identical. They have the same content, the same graphics, the same layout, the same case studies. The basic content (first 202 of 250 pages) is word for word, page for page IDENTICAL. The ONLY diffference between the 2 books is that "7 Methods" includes suggested solutions for the case studies (adding about 1 page for each of the 7 case studies). Do NOT buy "Intelligent Decision Support Methods". It is twice as expensive (hard cover vs soft cover) with no benefit.

10 of 10 people found the following review helpful:

5.0 out of 5 stars Revealing the Practical without Being Sidetracked by Gee-Wiz, September 3, 2002

By 

G. Gupton "defaultrisk" (New York City, USA) - See all my reviews
(REAL NAME)   

This review is from: Seven Methods for Transforming Corporate Data Into Business Intelligence (Paperback)

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.

9 of 9 people found the following review helpful:

4.0 out of 5 stars Good Intro to AI and Business Application, December 28, 2000

By 

"soomin" - See all my reviews

This review is from: Seven Methods for Transforming Corporate Data Into Business Intelligence (Paperback)

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.