| Introduction | |
This definitive, up-to-the-minute reference provides strategic, theoretical and practical insight into three of the most promising information management technologies--data warehousing, online analytical processing (OLAP), and data mining--showing how these technologies can work together to create a new class of information delivery system: the Information Factory. It comprehensively covers data warehouse design (using various approaches, models and indexing techniques), relational data base mining, data warehousing on the Web, and data replication. Several chapters discuss application development with popular OLAP tools. | |
| About the book | |
Improving data delivery is a top priority in business computing today. This comprehensive, cutting-edge guide can help?by showing you how to effectively integrate data mining and other powerful data warehousing technologies. You'll learn how to evaluate various data warehousing solutions (including SMP and MPP, parallel database management systems, metadata, OLAP, etc.) and how to leverage your data warehousing utility via the Internet, client/server computing, and various data mining tools. You?ll also learn how to compare different data mining technologies and products, and understand how they fit into your overall business and data processes. Intended for IS professionals as well as strategic planners, this fascinating book should serve as the essential reference to the standards, tools, technologies?and possibilities?of data warehousing today. | |
| About the author | |
Alex Berson is a senior information technology architect with over 20 years of experience in various areas of information technology including distributed client/server computing, database systems, parallel computing systems, object technology, data communications, and machine learning. He has successfully designed and implemented several large-scale data warehousing projects for major financial services companies. He is the author of several best-selling McGraw-Hill books, including Client/Server Architecture/2E and Sybase and Client/Server Computing. Stephen J. Smith is a director and architect responsible for the creation and delivery of two data mining products over the last decade?one for parallel supercomputers and the second for data warehouses with multidimensional databases. He is a well-respected expert in the field of data mining and their integration with the data warehouse. | |
| Table of contents | |
Part I: Foundation. Introduction to Data Warehousing. Client/Server Computing Model and Data Warehousing. Parallel Processors and Cluster Systems. Distributed DBMS Implementations. Client/Server RDBMS Solutions. Part II: Data Warehousing. Data Warehousing Components. Building a Data Warehouse. Mapping the Data Warehouse to a Multiprocessor Architecture. DBMS Schemas for Decision Support. Data Extraction, Cleanup, and Transformation Tools. Metadata. Part III: Business Analysis. Reporting and Query Tools and Applications. On-Line Analytical Processing (OLAP). Patterns and Models. Statistics. Artificial Intelligence. Part IV: Data Mining. Introduction to Data Mining. Decision Trees. Neural Networks. Nearest Neighbor and Clustering. Genetic Algorithms. Rule Induction. Selecting and Using the Right Technique. Part V: Data Visualization and Overall Perspective. Data Visualization. Putting It All Together. Appendices: A: Data Visualization. B: Big Data--Better Returns: Leveraging Your Hidden Data Assets to Improve ROI. C: Dr. E. F. Codd's 12 Guidelines for OLAP. D: Mistakes for Data Warehousing Managers to Avoid. | |
