Building Data Mining Applications

By Kurt Thearling, Alex Berson, Stephen J. Smith

Book Overview

This text provides comparison and contrast to different approaches and tools available for contemporary data mining. It offers a step-by-step plan to help readers develop a personalized approach. This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0071344446
• ISBN13: 9780071344449
• Release Date: December 1999
• Publisher: McGraw-Hill Companies
• Length: 600 Pages
• Weight: 2.27 lbs.
• Dimensions: 1.5" x 7.4" x 9.2"

Customer Reviews

Very useful and informative.

This book assumes sufficient knowledge of data warehouse and CRM. This book deals purely with Data Mining - one of the branches of Business Intelligence. A very good book that includes chapters on business value and business case for an enterprise wide Data Mining solution. Certainly is helpful to me in my goals to pursue data mining solutions for clients. Good understanding of a "profitable customer" is a prerequisite for...

This book helped me understand data mining

I have to admit, I am not deep technologist. My degree is an MBA, not an MS in statistics, so I was a bit hesitant when I ordered this book. Fortunately, Berson and his co-authors did a great job translating technology into relevant business issues. I now "get it," at least that's what some of my more techincally savvy colleagues say.I was looking for a good book that would help me understand what data mining could...

Finally "the book"

This book is valuable for 2 main reasons :- First, it is so rich in detail that it is an encyclopedia for Data Miner and CRM people. everything is described : tools, approaches, projects ...- Seconnd, an to me the key point : it is the only book that truly integrate CRM, data warehouse and data mining and still provide and intelligent reading !If you have a project wuth such flavour, or before embarking a CRM project, read...

Nice to see the focus on business apps

I've been actively following data mining for a few years now and have quite a few books on the subject (mostly algorithm books, though). This book was a good addition to my collection. Although it doesn't have the low-level algorithm details (there are no equations in the book), it does a very good job showing how mining can be applied to real problems. I thought the chapter (actually a case study) on customer retention...

Just what I needed. Five Stars!

I picked up a copy of this book (along with a few others) after my boss put me on a project to apply data mining to a churn problem we have been having. Unlike most of the other books I found, this one didn't limit itself to algorithms and statistics. It answered all my questions and was critical to a successful presentation I gave to our VP of marketing. I'm just about to start applying what I learned by deploying...