Business Intelligence

Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book:* Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence.* Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation.* Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies.* Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

ISBN 0470511389   Pages 436 ISBN13 9780470511381 (What's this?)   Volumes 1 Publisher John Wiley and Sons Ltd   Weight (grammes) 756 Imprint Wiley-Blackwell (an imprint of John Wiley & Sons Ltd)   Published in Chicester Format Hardback   Height (mm) 232 Publication date 20 Mar 2009   Width (mm) 160 Library of Congress 2008043814   Spine width (mm) 28 DEWEY 658.4038   Academic level Professional / Scholarly DEWEY edition DC22

I		Components of the decision-making process		1
1		Business intelligence		3
2		Decision support systems		21
3		Data warehousing		45
II		Mathematical models and methods		63
4		Mathematical models for decision making		65
5		Data mining		77
6		Data preparation		95
7		Data exploration		113
8		Regression		153
9		Time series		187
10		Classification		221
11		Association rules		277
12		Clustering		293
III		Business intelligence applications		317
13		Marketing models		319
14		Logistic and production models		361
15		Data envelopment analysis		385
Appendix A		Software tools		399
Appendix B		Dataset repositories		401
		References		403
		Index		413

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