Data Warehousing, Data Mining, and Olap

Overview

Optimize your organization's data delivery system! 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: Use data warehousing to establish a competitive advantage; Solve business problems faster by exploiting online analytical processing (OLAP); Evaluate various data warehousing solutions (including SMP and MPP,parallel ...
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Overview

Optimize your organization's data delivery system! 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: Use data warehousing to establish a competitive advantage; Solve business problems faster by exploiting online analytical processing (OLAP); Evaluate various data warehousing solutions (including SMP and MPP,parallel database management systems,metadata,OLAP,etc. ); Leverage your data warehousing utility via the Internet,client/server computing,and various data mining tools. In addition to providing a detailed overview and strategic analysis of the available data warehousing technologies,the book serves as a practical guide to data warehouse database design,star and snowflake schema approaches,multidimensional and mutirelational models,advanced indexing techniques,and data mining. You'll also learn how to compare different data mine 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 can be well relied upon as the essential reference to the standards,tools,technologies—and possibilities—of data warehousing today
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Product Details

  • ISBN-13: 9780070062726
  • Publisher: McGraw-Hill Companies, The
  • Publication date: 11/1/1997
  • Series: Series on Data Warehousing and Data Mana
  • Edition number: 1
  • Pages: 612
  • Product dimensions: 7.63 (w) x 9.58 (h) x 2.10 (d)

Table of Contents

Foreword
Preface
Ch. 1 Introduction to Data Warehousing 3
Ch. 2 Client/Server Computing Model and Data Warehousing 23
Ch. 3 Parallel Processors and Cluster Systems 47
Ch. 4 Distributed DBMS Implementations 67
Ch. 5 Client/Server RDBMS Solutions 89
Ch. 6 Data Warehousing Components 115
Ch. 7 Building a Data Warehouse 129
Ch. 8 Mapping the Data Warehouse to a Multiprocessor Architecture 151
Ch. 9 DBMS Schemas for Decision Support 169
Ch. 10 Data Extraction, Cleanup, and Transformation Tools 187
Ch. 11 Metadata 205
Ch. 12 Reporting and Query Tools and Applications 223
Ch. 13 On-Line Analytical Processing (OLAP) 247
Ch. 14 Patterns and Models 267
Ch. 15 Statistics 291
Ch. 16 Artificial Intelligence 317
Ch. 17 Introduction to Data Mining 333
Ch. 18 Decision Trees 351
Ch. 19 Neural Networks 375
Ch. 20 Nearest Neighbor and Clustering 407
Ch. 21 Genetic Algorithms 441
Ch. 22 Rule Induction 469
Ch. 23 Selecting and Using the Right Technique 493
Ch. 24 Data Visualization 517
Ch. 25 Putting It All Together 533
App. A: Glossary 561
App. B Big Data - Better Returns: Leveraging Your Hidden Data Assets to Improve ROI 579
App. C Dr. E.F. Codd's 12 Guidelines for OLAP 597
App. D 10 Mistakes for Data Warehousing Managers to Avoid 599
Bibliography 605
Index 609
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