Data mining is the process of finding useful patterns in data. The objective of data mining is to use discovered patterns to help explain current behavior ro to predict future outcomes. Several aspects of the data mining process can be studied. Be studied.

These include:
- Data gathering and storage
- Data selection and preparation
- Model building and testing
- Interpreting abd validating resuits
- Model application

A single book cannot concentrate on all areas of the data mining process. Although we furnish some detail about all aspects of data   mining and knowledge discovery, our primary focus is centered on model building and testing, as well as on interpreting and validating results.

Chapter 1 Data Mining: A first View
Chapter 2 Data Mining: A Clores Look
Chapter 3 Basic Data Mining Techniques
Chapter 4 An Excel-Based Data Mining Tool
Chapter 5 Knowledge Discovery in Databases
Chapter 6 The Data Warehouse
Chapter 7 Formal Evaluation Techniques
Chapter 8 Neural Networks
Chapter 9 Buiding Neural Networal
Chapter 10 Statistical Tecniques
Chapter 11 Specialized Tecniques
Chapter 12 Rule-Based Systems
Chapter 13 Managing Uncertainty in Rule-Based System
Chapter 14 Intelligent Agents

Appendix A The iDA Software
Appendix B Datasets for Data Mining
Appendix C Decision Tree Attribute
Appendix D Statistics for Performance Evaluation
Appendix E Excel Pivot Tables: Office 97