Discovering Data Mining: from Concept to Implementation / Edition 1

Discovering Data Mining: from Concept to Implementation / Edition 1

ISBN-10:
0137439806
ISBN-13:
9780137439805
Pub. Date:
09/18/1997
Publisher:
Prentice Hall

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Overview

Discovering Data Mining: from Concept to Implementation / Edition 1

This book teaches newcomers all they need to know to profit from today's powerful data mining technologies. Through extensive case studies and examples, you'll learn how companies are using data mining right now to achieve powerful results -- and how you can do it, too. Learn how data mining can help you build intimate relationships with customers that haven't existed for generations. Discover which areas of your business can benefit from data mining; the business, social and technical issues involved; how to prevent fraud and abuse; and how to make the most of outside consultants. The book also demonstrates IBM's powerful new Intelligent Miner tool and shows how it can be applied. Business and systems analysts; strategic planners; marketing executives; and other managers who can benefit from data mining.

Product Details

ISBN-13: 9780137439805
Publisher: Prentice Hall
Publication date: 09/18/1997
Edition description: BOOK & CD
Pages: 224
Product dimensions: 6.80(w) x 9.00(h) x 0.60(d)

Table of Contents

Figures
ix(2)
Foreword xi(4)
Preface xv
How This Book Is Organized xv(2)
About the Authors xvii(1)
Acknowledgments xviii(1)
Comments Welcome xix
Part 1. Introduction 1(38)
Chapter 1. Data Mining: the Basics
3(22)
Back to the Future
3(2)
Why Now?
5(1)
Changed Business Environment
5(7)
Drivers
7(2)
Enablers
9(3)
Toward a Definition
12(2)
Revolution or Evolution?
14(4)
What's So Different?
15(3)
Not So Different
18(1)
The Data Warehouse Connection
18(3)
The Data Warehouse
19(1)
The Data Mart
20(1)
From Data Warehouse to Data Mine
20(1)
From Data Mine to Data Warehouse
21(1)
Data Mining and Business Intelligence
21(1)
Where to from Here?
22(3)
Chapter 2. Down to Business
25(14)
Market Management Applications
26(4)
Improved Catalog TeleSales
27(1)
Sharper Customer Focus through Loyalty Cards
28(1)
Turning External Influences to Advantage
29(1)
Getting More Out of Store Promotions
30(1)
Risk Management Applications
30(4)
Forecasting Financial Futures
32(1)
Pricing Strategy in a Highly Competitive Market
33(1)
Fraud Management Applications
34(1)
Detecting Inappropriate Medical Treatments
34(1)
Detecting Telephone Fraud
35(1)
Emerging and Future Application Areas
35(2)
When Things Go Wrong!
37(2)
Part 2. Discovery 39(64)
Chapter 3. The Data Mining Process
41(20)
Before You Start
41(1)
The Process in Overview
42(3)
The Process in Detail
45(16)
Business Objectives Determination
45(2)
Data Preparation
47(8)
Data Mining
55(1)
Analysis of Results
56(3)
Assimilation of Knowledge
59(2)
Chapter 4. Face to Face with the Algorithms
61(28)
From Application to Algorithm
61(2)
Business Applications
62(1)
Data Mining Operations
62(1)
Data Mining Techniques
63(1)
Data Mining Operations
63(7)
Predictive Modeling
64(2)
Database Segmentation
66(2)
Link Analysis
68(1)
Deviation Detection
69(1)
Data Mining Techniques
70(19)
Predictive Modeling: Classification
70(6)
Predictive Modeling: Value Prediction
76(2)
Database Segmentation: Demographic Clustering
78(1)
Database Segmentation: Neural Clustering
79(1)
Link Analysis: Associations Discovery
80(3)
Link Analysis: Sequential Pattern Discovery
83(2)
Link Analysis: Similar Time Sequence Discovery
85(1)
Deviation Detection: Visualization
86(2)
Deviation Detection: Statistics
88(1)
Chapter 5. Evaluating Vendor Solutions
89(14)
The Value of Technology
90(1)
Data Mining Tools
90(9)
Types of Data Mining Tools
91(2)
Data Mining Process Support
93(4)
Technical Considerations
97(2)
Conclusions
99(1)
Data Mining Applications
99(1)
Generic Applications
99(1)
Industry-Specific Applications
100(1)
Conclusions
100(1)
Data Mining Services
100(3)
Consultancy Services
100(1)
Implementation Services
101(1)
Education Services
101(1)
Related Services
102(1)
Conclusions
102(1)
Part 3. Implementation 103(78)
Chapter 6. Case Studies
105(20)
Preventing Fraud and Abuse
106(8)
Background
106(1)
Business Objectives Identification
106(1)
Data Preparation
107(1)
Data Mining
108(3)
Analysis of Results and Assimilation of Knowledge
111(2)
Summary of Findings and Benefits
113(1)
Improving Direct Mail Responses
114(11)
Background
114(1)
Business Objectives Identification
114(2)
Data Preparation
116(1)
Data Mining
117(3)
Analysis of Results and Assimilation of Knowledge
120(3)
Summary of Findings and Benefits
123(2)
Chapter 7. Getting Started with Data Mining
125(16)
Are You Ready for Data Mining?
126(1)
Challenges
127(2)
Social Issues
127(1)
Business Issues
128(1)
Technical Issues
128(1)
Planning Your Approach
129(3)
The Business Case
132(1)
Selecting a Candidate Application
133(1)
In-House or Outsource?
134(2)
Assessing Vendor Solutions
136(1)
Skills and Timescales
136(2)
Critical Success Factors
138(1)
Conclusions
139(2)
Appendix A. IBM's Data Mining Solution
141(26)
Data Mining Tools
141(14)
Intelligent Miner
142(4)
Intelligent Miner User Scenario
146(9)
Companion Products
155(6)
Intelligent Decision Server
155(2)
Visual Warehouse
157(3)
Parallel Visual Explorer
160(1)
Diamond
160(1)
Visualization Data Explorer
160(1)
Data Mining Applications
161(2)
Generic Applications
161(1)
Industry-Specific Applications
161(2)
Data Mining Services
163(2)
Consultancy Services
163(1)
Implementation Services
163(1)
Education Services
164(1)
Related Services
164(1)
Emerging Technologies
165(2)
Text and Media Mining
165(1)
Internet Mining
166(1)
Miscelleanous
166(1)
Appendix B. Special Notices
167(2)
Appendix C. Further Reading and Resources
169(12)
Books
169(2)
Articles
171(2)
Internet Resources
173(1)
Vendor-Sponsored Sites
173(1)
Vendor-Independent Sites
174(1)
ITSO Publications
174(1)
Redbooks on CD-ROMs
174(1)
How to Get ITSO Redbooks
175(1)
How IBM Employees Can Get ITSO Redbooks
175(3)
How Customers Can Get ITSO Redbooks
178(2)
IBM Redbook Order Form
180(1)
Glossary 181(6)
List of Abbreviations 187(2)
Index 189

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