A01=Zhengxin Chen
advanced data analysis strategies
algorithm
analysis
Apriori Algorithm
artificial intelligence methods
Association Rule Mining
Association Rules
Author_Zhengxin Chen
Bitmap Indexing
Building Data Warehouses
business intelligence systems
Category=UMZ
Category=UN
Category=UNF
Category=UY
Category=UYQ
computational intelligence techniques
Computer Science Perspective
cube
Data Cubes
Data Marts
Data Mining
Data Model
Data Warehouse Design
Data Warehouse Environment
Data Warehousing
decision support systems
Entity Sets
environment
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
genetic
graduate level textbook
Intelligent Data Analysis
Intelligent Data Warehousing
Item Set
knowledge discovery process
mart
materialized
mining
Multidimensional Data Model
MV
Rough Set Theory
SQL Query
Star Schema
view
View Graph
View Maintenance
warehouse
Web Mining
Product details
- ISBN 9780849312045
- Weight: 630g
- Dimensions: 156 x 234mm
- Publication Date: 13 Dec 2001
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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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.
