Building Data Mining Applications

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 an enterprise wide data mining solution - which is emphasized in this book neatly. Can be used to educate marketing/sales/operations executives about data mining concepts and principles. Unless there's an executive buy-in, the concept will not sell in an organization. Business values and business case chapters will help one is selling this concept to higher-ups and help associates understand data mining in theory.My theory is that, data mining implementations would help organizations coming out of this economic mess, in reducing marketing/sales/operating costs based on understanding the customer profitability and customer segmentation. Unless you spend on your customers, customer loyality is not assured. Why spend a lot on all customers when not all are created equal? This is the book that will justify such questions and pave the way for a profitable business.

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 bring to our expanding e-commerce business channel. We already have several CRM software systems in place (marketing automation, call center, personalized web site) and this book helped me understand the analytic foundation that is built into the existing systems.One final thing. Although this book does not claim to be a reference for data mining algorithms, it does have a pair of well written "techniques" chapters. These two chapters go though a long list of algorithms (clustering, CART, CHAID, neural networks, and more) and provide a nice introduction. For me it was perfect.

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 this before the first meeting

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 was exceptional.

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 a churn campaign and don't think I would be where I am without this book. I give it a five star recommendation.