UNIT – 1………………..7
Introduction to Data Warehousing
1.1 Introduction
1.2 What is Data Warehouse? Definition
1.3 Multidimensional Data Model
1.4 OLAP Operations
1.5 Warehouse Schema
1.6 Data Warehouse Architecture
1.7 Warehouse Server
1.8 Metadata
1.9 OLAP Engine
1.10 Data Warehouse Backend Process. .

UNIT – 2……………………………19
Introduction to Data Mining
2.1 What is Data Mining?
2.2 History of Data Mining
2.3 Types of Data
2.4 Data Mining Techniques
2.5 Data Mining Implementation Process
2.6 Data Mining vs Machine Learning

UNIT – 3………………………………………29
Basics of Data Mining and Models
3.1 Introduction to Data Mining Functionalities
3.2 Issues in Data Mining
3.3 Data Mining Architecture
3.4 Data Mining Models
3.5 Types of data mining models
3.6 Interestingness of Patterns – Classification of Data Mining Systems – Data
Mining Task.

UNIT – 4………………………………………………38
Association Rule Mining
4.1 Mining Frequent Patterns
4.2 Associations and correlations
4.3 Mining Methods4.4 Mining Various Kinds of Association Rules
4.5 Correlation Analysis
4.6 Constraint Based Association Mining

UNIT – 5…………………………………………………53
Classification of Data Mining
5.1 Classification and Prediction – Basic concepts
5.2 Decision Tree Induction
5.3 Bayesian Classification
5.4 Rule Based classification
5.5 Classification by Back propagation
5.6 Support Vector Machines

UNIT – 6………………………………………………69
Clustering and Applications
6.1 Cluster analysis
6.2 Categorization of Major Clustering methods
6.3 K-means partitioning methods
6.4 Hierarchical Methods- Data Mining Applications