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

by Michael J.A. Berry, Gordon S. Linoff

Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis

Genres: Business, Computer Science, Research, Nonfiction, Technology, Technical, Management

672 pages, Kindle Edition

First published May 27, 1997

Reviews

[Arief Nake Bahadi · Rating 3 out of 5]

baca buku karena sedang mengerjakan skripsi data mining
buku ini cukup bagus, berisi mengenai contoh data mining dan implementasinya dalam corporate
teori dijelaskan dengan cukup baik disertai kelebihan dan kekurangan tiap klasifikasi data mining
buku ini lebih ditujukan kepada pemula data mining karena hanya berisikan teori
sedangkan algoritma tidak dicantumkan

[Omer Zeybek · Rating 5 out of 5]

Great reference book for marketing analytics

[Fountain Of Chris · Rating 4 out of 5]

It's a textbook, so it's both comprehensive and dry. Dated by now, but it was a good refresher of my predictive analytics and stats courses.

[Meta Brown · Rating 5 out of 5]

This is a solid primer in data mining! The author knows the material well, and writes clearly.

The book includes a generous dose of introductory material, something many other titles omit, but which most readers need. And it's written so that it can be understood by newcomers to the topic.

This book is best for those who have some significant technical grounding, such as training in statistics, programming, or databases. If you're an IT professional, programmer or experienced data analyst who wants to get a grasp of data mining, reading this book would be an excellent way to begin.

If you are a business person who wants a beginner's book to understand data mining concepts and perhaps try it yourself, but you're not yet a hands-on data analyst, this book may not be what you have in mind. You might prefer to choose another book to start, or to read just portions of this one to suit your own comfort zones.

[Mahan · Rating 5 out of 5]

It covers almost every aspect of data mining. It is clear, precise, goes to the point, and sometimes goes into some depth. If you are a marketing person, it will give you a very refined idea of what can be done with data mining, and what does it involves for your company ( remember the first thing you need is DATA!!). If you are an academic person, you will get a general idea of the different kinds of data analysis. You won't see any formulae or algorithms, after reading this book look for details somewhere else.

[Andras Morvay · Rating 4 out of 5]

This had some good concepts that I could utilize in my work, namely how to deal with null values, customer signatures, intros into regression, clustering, decision trees.

[Shiina]

read some case studies, not very interested