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Intelligent Data Warehousing : From Data Preparation to Data Mining - Zhengxin Chen

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Intelligent Data Warehousing

Name: Intelligent Data Warehousing
Brand: CRC PR INC
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From Data Preparation to Data Mining

By: Zhengxin Chen

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Hardcover | 13 December 2001 | Edition Number 1

At a Glance

Hardcover
256 Pages

Dimensions(cm)
23.4 x 15.6 x 1.91

Hardcover

RRP $305.00

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Effective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in fact many of its advances have and will continue to come from the computer science arena.

Intelligent Data Warehousing presents the state of the art in data warehousing research and practice from a perspective that integrates business applications and computer science. It brings the intelligent techniques associated with artificial intelligence (AI) to the entire process of data warehousing, including data preparation, storage, and mining. Part I provides an overview of the main ideas and fundamentals of data mining, artificial intelligence, business intelligence, and data warehousing. Part II presents core materials on data warehousing, and Part III explores data analysis and knowledge discovery in the data warehousing environment, including how to perform intelligent data analysis and the discovery of influential association patterns.

Bridging the gap between theoretical research and business applications, this book summarizes the main ideas behind recent research developments rather than setting forth technical details, and it presents case studies that show the how-to''s of implementing these ideas. The result is a practical, first-of-its-kind book that brings together scattered research, unites MIS with computer science, and melds intelligent techniques with data warehousing.

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You Can Find This Book In

Non-Fiction Computing & I.T.Databases Data Warehousing Data Mining Computer Science Artificial Intelligence Computer Programming & Software Development Software Engineering


Introduction	p. 3
Why this book is needed	p. 3
Features of the book	p. 5
Why intelligent data warehousing	p. 5
Organization of the book	p. 6
How to use this book	p. 7
References	p. 8
Enterprise intelligence and artificial intelligence	p. 11
Overview	p. 11
Data warehousing and enterprise intelligence	p. 11
Historical development of data warehousing	p. 12
Basic elements of data warehousing	p. 14
Databases and the Web	p. 15
Basics of artificial intelligence and machine learning	p. 21
Data warehousing with intelligent agents	p. 26
Data mining, CRM, Web mining, and clickstream	p. 29
The future of data warehouses	p. 34
Summary	p. 35
References	p. 36
From DBMS to data warehousing	p. 39
Overview	p. 39
An overview of database management systems	p. 39
Advances in DBMS	p. 46
Architecture and design of data warehouses	p. 52
Data Marts	p. 55
Metadata	p. 58
Data warehousing and materialized views	p. 60
Data warehouse performance	p. 64
Data warehousing and OLAP	p. 66
Summary	p. 68
References	p. 68

Data preparation and preprocessing	p. 73
Overview	p. 73
Schema and data integration	p. 73
Data pumping	p. 75
Middleware	p. 76
Data quality	p. 77
Data cleansing	p. 78
Dealing with data inconsistency in multidatabase systems	p. 83
Data reduction	p. 84
Case study: data preparation for stock food chain analysis	p. 85
Web log file preparation	p. 93
Summary	p. 96
References	p. 96
Building data warehouses	p. 97
Overview	p. 97
Conceptual data modeling	p. 97
Data warehouse design using ER approach	p. 100
Aspects of building data warehouses	p. 105
Data cubes	p. 111
Summary	p. 113
References	p. 113
Basics of materialized views	p. 117
Overview	p. 117
Data cubes	p. 118
Using a simple optimization algorithm to select views	p. 125
Aggregate calculation using preconstructed data structures in data cubes	p. 127
Case study: view selection for a human service data warehouse	p. 130
Summary	p. 145
References	p. 145
Advances in materialized views	p. 147
Overview	p. 147
Data warehouse design through materialized views	p. 148
Maintenance of materialized views	p. 151
Consistency in view maintenance	p. 157
Integrity constraints and active databases	p. 163
Dynamic warehouse design	p. 165
Implementation issues and online updates	p. 168
Data cubes	p. 169
Materialized views in advanced database systems	p. 173
Relationship with mobile databases	p. 175
Other issues	p. 175
Summary	p. 177
References	p. 177

Intelligent data analysis	p. 187
Overview	p. 187
Basics of data mining	p. 188
Case study: stock food chain analysis	p. 192
Case study: rough set data analysis	p. 195
Recent progress of data mining	p. 204
Summary	p. 206
References	p. 206
Toward integrated OLAP and data mining	p. 209
Overview	p. 209
Integration of OLAP and data mining	p. 209
Influential association rules	p. 210
Significance of influential association rules	p. 212
Reviews of algorithms for discovery of conventional association rules	p. 214
Discovery of influential association rules	p. 216
Bitmap indexing and influential association rules	p. 220
Mining influential association rules using bitmap indexing (IARMBM)	p. 223
Summary	p. 226
References	p. 226
Index	p. 229
Table of Contents provided by Syndetics. All Rights Reserved.

Intelligent Data Warehousing

From Data Preparation to Data Mining

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

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