Data Warehouse and Data Mining Technology

Author: Liu Xiang
Publisher:
Publish Date: 2005-08-01
Features: Enterprise informatization is a revolutionary project. This book takes enterprise informatization as its starting point, introducing the concepts, architecture, development methods, and steps of ERP data warehouse systems. The book is divided into 9 chapters. Chapter 1 primarily introduces the development history of enterprise informatization, the concepts, characteristics, differences, connections, and applications of data warehouses in enterprise environments. Chapter 2 covers data warehouse development tools—Microsoft SQL Server 2000's data warehouse architecture and application techniques. Chapter 3 discusses data warehouse structures and their creation, including data warehouse databases, fact tables, dimension tables, and multidimensional cubes. Chapter 4 explains the complete development process of data warehouses, including project system planning, user requirement determination, system analysis, system design, system implementation, system testing, and expansion. Chapter 5 introduces the basic concepts of DTS, the creation, configuration, and use of DTS packages, and how to automatically transfer data from data sources to data warehouses using DTS packages. Chapter 6 covers OLAP's MDX representation and implementation, including the MDX language representation and implementation of basic OLAP analytical actions and OLAP front-end presentation methods, providing numerous MDX language program examples. Chapter 7 introduces the fundamentals of data mining, including the concepts, techniques, tools, methods, and steps of data mining. Chapter 8 discusses common knowledge discovery techniques and data mining methods, including dependency analysis, clustering analysis, neural network-based data mining methods, genetic algorithm-based data mining methods, and rough set-based data mining methods. Chapter 9 covers SQL Server 2000 data mining techniques. This book emphasizes practical engineering, is highly practical, and helps readers comprehensively master the methods and steps of data warehouse construction and data mining, enabling the development of data warehouse systems with practical value. This book is suitable as a textbook for undergraduate students in information management and information systems, e-commerce, logistics management, and related disciplines in higher education institutions. It can also serve as a teaching material for graduate students in finance and management-related fields. Additionally, it holds significant reference value for data warehouse and data mining professionals and researchers in enterprises and institutions.