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Data Mining Techniques: For Marketing, Sales, and Customer Support (Englisch) Taschenbuch – Juni 1997

3.7 von 5 Sternen 9 Kundenrezensionen

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Produktbeschreibungen

Pressestimmen

"The book thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions." (Fathbrain.com; Ganthead.com, 9/01)

Synopsis

Who will remain a loyal customer and who won't? What kind of marketing approach is most likely to increase sales? What can customer buying patterns tell us about improving our inventory control? What type of credit approval process will work best for us and our customers? The answers to these and all your crucial business questions lie buried in your company's information systems. This book supplies you with powerful tools for mining them. Data Mining Techniques thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions. One of the first practical guides to mining business data, it describes techniques for detecting customer behavior patterns useful in formulating marketing, sales, and customer support strategies. While database analysts will find more than enough technical information to satisfy their curiosity, technically savvy business and marketing managers will find the coverage eminently accessible.

Here's your chance to learn all about: How leading companies across North America are using data mining to beat the competition How each tool works, and how to pick the right one for the job Seven powerful techniques -cluster detection, memory-based reasoning, market basket analysis, genetic algorithms, link analysis, decision trees, and neural nets How to prepare data sources for data mining, and how to evaluate and use the results you get Data Mining Techniques shows you how to quickly and easily tap the gold mine of business solutions lying dormant in your information systems.

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Format: Taschenbuch
The authors explain in a detailed way the most popular Data Mining techniques. The topics about Neuronal Networks, Decision Trees, Market-Basket Analysis and Memory-Based Reasoning are excellent. I think the topic Genetic Algorithms could be a bit more developed, but for the beginner is a good first overview. I have missed a topic about fuzzy logic. Given that the 90% of Data Mining projects are based on Marketing (1:1), the book is absolutely suitable for starting with these concepts, although I feel the book can be used in any other field (Just-In-Time Inventory, Demand Forecasting, Supply Value Chain, etc.)

In my opinion, it was very useful for my work and I considered it as a reference book.
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Format: Taschenbuch
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.
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Format: Taschenbuch
This book is chock full of the syntactic ambiguities which make relatively simple concepts, such as MBR, difficult to explore.
e.g. "That is, 80 percent of the codes assigned by MBR were correct, but the cost was that 28 percent of the codes assigned were incorrect."
Luckily, there's a picture explaining the mess.
The ideas are here, but Berry and Linoff need to hire a real writer. I guess, smart folks like these guys have a tough time communicating with the common man?
- Merv
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Von Ein Kunde am 25. Februar 1999
Format: Taschenbuch
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.
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This book labors to explain that Data Mining is possible. It spends 3 chapters explaining the business process flow of data mining as: 1. Figure out your business problem 2. data mine to figure out what to do 3. do it 4. measure to see if you did anything.
It's nicely written, but VERY BASIC
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