Data mining techniques
for marketing, sales, and customer support
By Michael J. A. Berry

"Data mining techniques" is published by Wiley in 1997 - New York, it has 454 pages and the language of the book is English.
“Data mining techniques” Metadata:
- Title: Data mining techniques
- Author: Michael J. A. Berry
- Language: English
- Number of Pages: 454
- Publisher: Wiley
- Publish Date: 1997
- Publish Location: New York
“Data mining techniques” Subjects and Themes:
- Subjects: ➤ Data processing - Marketing - Business - Data mining - Informatique - INDUSTRIAL MANAGEMENT - Data-Warehouse-Konzept - Exploration de données - Klantenservice - Gestion - Exploration de données (Informatique) - Marketing, data processing
Edition Specifications:
- Pagination: x, 454 p. :
Edition Identifiers:
- The Open Library ID: OL667851M - OL2656915W
- Online Computer Library Center (OCLC) ID: 36755821
- Library of Congress Control Number (LCCN): 97013601
- ISBN-10: 0471179809
- All ISBNs: 0471179809
AI-generated Review of “Data mining techniques”:
"Data mining techniques" Description:
The Open Library:
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, and 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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