Data Warehousing data mining and OLAP

PART I: FOUNDATION


Chapter 1 Introduction to Data Warehousing
Chapter 2 Client/Server Computing Model and Data Warehousing
Chapter 3 Parallel Processors and Cluster Systems
Chapter 4 Distributed DBMS Implementations
Chapter 5 Client/Server RDBMS Solutions


PART II: DATA WAREHOUSING

Chapter 6 Data Warehousing Components
Chapter 7 Building a Data Warehouse
Chapter 8 Mapping the Data Warehouse to a Multiprocessor Architecture
Chapter 9 DBMS Schemas for Decision Support
Chapter 10 Data Extraction, Cleanup, and Transformation Tools
Chapter 11 Metadata


PART III: BUSINESS ANALYSIS

Chapter 12 Reporting and Query Tools and Applications
Chapter 13 On-Line Analytical Processing (OLAP)
Chapter 14 Patterns and Models
Chapter 15 Statistics
Chapter 16 Artificial Intelligence


PART IV: DATA MINING

Chapter 17 Introduction to Data Mining
Chapter 18 Decision Trees
Chapter 19 Neural Networks
Chapter 20 Nearest Neighbor and Clustering
Chapter 21 Genetic Algorithms
Chapter 22 Rule Induction
Chapter 23 Selecting and Using the Right Technique


PART V: DATA VISUALIZATION AND OVERALL PERSPECTIVE

Chapter 24 Data Visualization
Chapter 25 Putting It All Together