Intelligent Data Warehousing: From Data Preparation to Data Mining

Intelligent Data Warehousing: From Data Preparation to Data Mining

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 subdisc...

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Tác giả chính: Chen, Zhengxin
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: CRC Press 2009
Truy cập trực tuyến:http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1519
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Thư viện lưu trữ: Thư viện Trường Đại học Đà Lạt
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description 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. A CRCnetBASE Product
format Book
author Chen, Zhengxin
spellingShingle Chen, Zhengxin
Intelligent Data Warehousing: From Data Preparation to Data Mining
author_facet Chen, Zhengxin
author_sort Chen, Zhengxin
title Intelligent Data Warehousing: From Data Preparation to Data Mining
title_short Intelligent Data Warehousing: From Data Preparation to Data Mining
title_full Intelligent Data Warehousing: From Data Preparation to Data Mining
title_fullStr Intelligent Data Warehousing: From Data Preparation to Data Mining
title_full_unstemmed Intelligent Data Warehousing: From Data Preparation to Data Mining
title_sort intelligent data warehousing: from data preparation to data mining
publisher CRC Press
publishDate 2009
url http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1519
_version_ 1757661791461048320
spelling oai:scholar.dlu.edu.vn:DLU123456789-15192009-12-03T09:29:10Z Intelligent Data Warehousing: From Data Preparation to Data Mining Chen, Zhengxin 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. A CRCnetBASE Product Part I: INTRODUCTION Why this Book is Needed Features of the Book Why Intelligent Data Warehousing Organization of the Book How to Use this Book ENTERPRISE INTELLIGENCE AND ARTIFICIAL INTELLIGENCE Overview Data Warehouse and Business Intelligence Historical Development of Data Warehousing Basic Elements of Data Warehousing Databases and the Web Basics of Artificial Intelligence and Inductive Machine Learning Data Warehousing with Intelligent Agents Data Mining, CRM, Web Mining and Clickstream The Future of Data Warehouses BASICS OF DATA WAREHOUSING Overview An Overview of Database Management Systems Advances in DBMS Architecture and Design of Data Warehouses Data Marts Metadata Data Warehousing and Materialized Views Data Warehouse Performance Data warehousing and OLAP Part II: DATA PREPARATION AND PREPROCESSING Overview Schema and Data Integration Data Pumping Middleware Data Quality Data Cleansing Uncertainty and Inconsistency Data Reduction Case Study: Data Preparation for Stock Food Chain Analysis Web log File Preparation References BUILDING DATA WAREHOUSES Overview Conceptual Data Modeling Data Warehouse Design Using ER Approach Aspects of Building Data Warehouses Data Cubes BASICS OF MATERIALIZED VIEWS Overview Data Cubes Using Simple Optimization Algorithm to Select Views Aggregates Calculation Using Pre-Constructed Data Structures in Data Cubes View Selection for a Human Service Data Warehouse ADVANCES IN MATERIALIZED VIEWS Overview Data Warehouse Design Through Materialized Views Maintenance of Materialized Views Consistency in View Maintenance Integrity Constraints and Active Databases Dynamic Warehouse Design Implementation Issues and Online Updates Data Cubes Materialized Views in Advanced Database Systems Relationship with Mobile Databases Other Issues Part III: INTELLIGENT DATA ANALYSIS Overview Basics of Data Mining Case Study: Stock Food Chain Analysis Case Study: Rough Set Data Analysis Recent Progress of Data Mining TOWARD INTEGRATED OLAP AND DATA MINING Overview Integration of OLAP and Data Mining Influential Association Rules Significance of Influential Association Rules Reviews of Algorithms for Discovery of Conventional Association Rules Discovery of Influential Association Rules Bitmap Indexing and Influential Association Rules Mining Influential Association Rules Using Bitmap Indexing INDEX Each chapter also contains a Summary section and Reference 2009-12-03T09:29:10Z 2009-12-03T09:29:10Z 2001 Book http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/1519 en application/rar CRC Press

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