Data Mining Storage Management Books : Data Mining Techniques: for Marketing, Sales and Customer Relationship Management: For Marketing, Sales and Customer Relationship Management

Data Mining Techniques: for Marketing, Sales and Customer Relationship Management: For Marketing, Sales and Customer Relationship Management

£19.06


A must-have book for your technical library - Anyone interested in automating and improving decisions should have this book. It is one of the classic works on data mining and well worth the read. I really liked the book both because it is well written and because, although it drilled into a fair amount of detail about some of the techniques, it started each new section off at a high level. This allows someone without a statistical background, such as me, to read as far as I can in each section and then skip ahead to the next technique. This is a nice change from books that simply get more and more detailed as page follows page, preventing you from gaining an overview of the subject. The book introduces data mining and a methodology for applying it, talks about some of the applications in Marketing, Sales, and Customer Relationship Management (as the subtitle puts it), walks through some statistical techniques and then spends the bulk of the book on various data mining techniques. It wraps up with a nice summary of how data mining plays with other technologies and with some practical advice on getting started. One of the best summaries of where data mining fits is given early in the book where an enterprise is encouraged to: - Notice what its customers are doing - Remember what it and its customers have done over time - Learn from what it has remembered - Act on what if has learned to make customers more profitable The authors point out that Data Mining is focused on the Learn stage or, as they put it data mining suggests but businesses decide. The methodology section, and the subsequent notes that relate to applying these techniques in real life, talked about the feedback loops between steps in data mining - there is not a linear waterfall sequence of steps but constant iteration and learning. They also emphasized the importance of finding the right business problem at the beginning - start as someone once said, with the end in mind. This was reiterated when they quote Voltaire who said Le mieux est l ennemi du bien (The best is the enemy of good). In other words, don t get hung up on trying to find the perfect algorithm, perfect answer. Instead build something that is good, that works, and learn and improve over time. The authors made a big point out of the value of data mining for mass intimacy, where you want to treat customers differently and there is a business reason to do so but where customers are too numerous to be assigned to staff. One of the issues they pointed out was that staff must be trained in customer interaction skills while also using all the data you have. The value of data mining in building a customer-centric organization cannot be overestimated.

The best intro to data mining I know of - This book does what few others manage - namely, go through an immense amount of material using almost no math at all, so it s a pleasure to read, and discussing not just what the techniques are, but what they do, what they re good for, and what weaknesses each has. On the other hand, the book gives enough detail on each method that it s completely clear how the math goes, and I could (and did) write the math easily for the methods I was interested in.

Excellent book taking Statistical headache out of Datamining - As a DM Consultant, this book is a must read for anybody new to Data Mining, who wants to fully understand the techniques but doesn t want to get bogged down in specific statistical methods and algorythms. Totally business focused which will leave academics frustrated.

Excellent discussion of a wide variety of techniques - Provides an excellent discussion of a wide variety of techniques and their applicability to business problems.

Not mathematical enough. - Very disappointing, if you re looking for a mathematically oriented book. In fact it avoids math like the plague. It s therefore ideally suited to: (a) project managers who don t really want to do any serious work themselves, and (b) people who want to drop words at cocktail parties to impress people. Totally unsuited to the serious researcher.




Data Mining Techniques: for Marketing, Sales and Customer Relationship Management: For Marketing, Sales and Customer Relationship Management