Microsoft Data Mining

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Overview

Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management.

Audience: Professional data analysts; DBAs, senior marketing managers, electronic direct marketing specialists; SQL Server programmers, administrators, and system designers.

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Overview

Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management.

Audience: Professional data analysts; DBAs, senior marketing managers, electronic direct marketing specialists; SQL Server programmers, administrators, and system designers.

Editorial Reviews

Booknews
The inventor of one of the first data mining decision tree products, de Ville approaches data mining from the perspective of business analysts and information technology professionals using Microsoft data management technologies. He explains the features of several software packages and suggests best practices for using them. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Product Details

  • ISBN-13: 9781555582425
  • Publisher: Elsevier Science
  • Publication date: 4/1/2001
  • Pages: 336
  • Product dimensions: 0.70 (w) x 7.00 (h) x 10.00 (d)

Table of Contents

The Big Picture: Data Mining's Benefits, History, and Limitations
Data Mining Tools and Techniques and the Microsoft Data Mining Arsenal: Windows DNA 2000, OLE DB for DM, Data Mining Models, ADO, SQL Server Data Mining Extensions
The Data Mining Process: Business Objective Understanding
Managing the Data Mining Project: Preparing the Data for Analysis
Modeling, Testing and Validation
Results Deployment
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