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Monday, January 23, 2012

Data Mining and Warehousing






S. Prabhu
N. Venkatesan

CONTENTS
Preface vii
Acknowledgement ix
Chapter 1 Data Mining and Warehousing Concepts 1-7
1.1 Introduction 1
1.2 Data Mining Definitions 2
1.3 Data Mining Tools 3
1.4 Applications of Data Mining 3
1.5 Data Warehousing and Characteristics 4
1.6 Data Warehouse Architecture 6
Exercise 7
Chapter 2 Learning and Types of Knowledge 8-13
2.1 Introduction 8
2.2 What is Learning? 8
2.3 Anatomy of Data Mining 9
2.4 Different Types of Knowledge 12
Exercise 13
Chapter 3 Knowledge Discovery Process 14-22
3.1 Introduction 14
3.2 Evaluation of Data Mining 15
3.3 Stages of the Data Mining Process 15
3.4 Data Mining Operations 20
3.5 Architecture of Data Mining 20
Exercise 22
Chapter 4 Data Mining Techniques 23-53
4.1 Introduction 23
4.2 Classification 23
4.3 Neural Networks 23
4.4 Decision Trees 24
4.5 Genetic Algorithm 32
4.6 Clustering 34
4.7 Online Analytic Processing (OLAP) 45
4.8 Association Rules 46
4.9 Emerging Trends in Data Mining 51
4.10 Data Mining Research Projects 52
Exercise 53
Chapter 5 Real Time Applications and Future Scope 54-62
5.1 Applications of Data Mining 54
5.2 Future Scope 59
5.3 Data Mining Products 61
Exercise 62
Chapter 6 Data Warehouse Evaluation 63-71
6.1 The Calculations for Memory Capacity 63
6.2 Data, Information and Knowledge 65
6.3 Fundamental of Database 65
6.4 OLAP and OLAP Server 68
6.5 Data Warehouses, OLTP, OLAP and Data Mining 69
Exercise 71
Chapter 7 Data Warehouse Design 72-85
7.1 Introduction 72
7.2 The Central Data Warehouse 72
7.3. Data Warehousing Objects 74
7.4 Goals of Data Warehouse Architecture 77
7.5 Data Warehouse Users 78
7.6 Design the Relational Database and OLAP Cubes 79
7.7 Data Warehousing Schemas 81
Exercise 85
Chapter 8 Partitioning in Data Warehouse 86-94
8.1 Introduction 86
8.2 Hardware Partitioning 86
8.3 RAID Levels 88
8.4 Software Partitioning Methods 92
Exercise 94
Chapter 9 Data Mart and Meta Data 95-100
9.1 Introduction 95
9.2 Data Mart 95
9.3 Meta Data 96
9.4 Legacy Systems 100
Exercise 100
Chapter 10 Backup and Recovery of the Data Warehouse 101-105
10.1 Introduction 101
10.2 Types of Backup 101
10.3 Backup the Data Warehouse 102
10.4 Data Warehouse Recovery Models 104
Exercise 105
Chapter 11 Performance Tuning and Future of Data Warehouse 106-109
11.1 Introduction 106
11.2 Prioritized Tuning Steps 106
11.3 Challenges of the Data Warehouse 107
11.4 Benefits of Data Warehousing 108
11.5 Future of the Data Warehouse 108
11.6 New Architecture of Data Warehouse 109
Exercise 109
Appendix A Glossary 110-114
Appendix B Multiple-Choice Questions 115-116
Appendix C Frequently Asked Questions & Answers 117-119
Appendix D Model Question Papers 120-124
Bibliography 125-126
Index 127-129

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