UNIT I DATA WAREHOUSING
Data warehousing Components -Building a Data warehouse -- Mapping the Data Warehouse to a Multiprocessor Architecture - DBMS Schemas for Decision Support - Data Extraction, Cleanup, and Transformation Tools -Metadata.
UNIT II BUSINESS ANALYSIS
Reporting and Query tools and Applications - Tool Categories - The Need for Applications - Cognos Impromptu - Online Analytical Processing (OLAP) - Need - Multidimensional Data Model - OLAP Guidelines - Multidimensional versus Multi relational OLAP - Categories of Tools - OLAP Tools and the Internet.
UNIT III DATA MINING
Introduction - Data - Types of Data - Data Mining Functionalities - Interestingness of Patterns - Classification of Data Mining Systems - Data Mining Task Primitives - Integration of a Data Mining System with a Data Warehouse - Issues -Data Preprocessing.
UNIT IV ASSOCIATION RULE MINING AND CLASSIFICATION
Mining Frequent Patterns, Associations and Correlations - Mining Methods - Mining various Kinds of Association Rules - Correlation Analysis - Constraint Based Association Mining - Classification and Prediction - Basic Concepts - Decision Tree Induction - Bayesian Classification - Rule Based Classification - Classification by Back propagation - Support Vector Machines - Associative Classification - Lazy Learners - Other Classification Methods - Prediction.
UNIT V CLUSTERING AND TRENDS IN DATA MINING
Cluster Analysis - Types of Data - Categorization of Major Clustering Methods - K-means- Partitioning Methods - Hierarchical Methods - Density-Based Methods -Grid Based Methods - Model-Based Clustering Methods - Clustering High Dimensional Data - Constraint - Based Cluster Analysis - Outlier Analysis - Data Mining Applications.
