DATA WAREHOUSING AND DATA MINING
SYLLABUS
UNIT I
Introduction - Data Mining - Functionalities - Classification of data mining systems - Major issues in data mining. Data warehouse and OLAP technology for data mining:
What is a data warehouse - A Multi dimensional model - Data Warehouse Architecture - Data Warehouse Implementation - Further development of Data cube technology.
UNIT II
Data preprocessing: Data cleaning - Data integration and transformation - Data reduction - Discretisation and concept hierarchy generation. Data Mining Primitives: What defines
a data mining tasks.
UNIT III
Mining Association Rules in Large Databases: Association rule mining - Mining single dimensional Boolean association rule from transactional databases Mining
Multidimensional association rules from relational databases and data warehouses.
UNIT IV
Classification and Prediction: What is classification - Issues regarding classification -Classification by decision tree induction - Bayesian classification.
UNIT V
Cluster Analysis: Types of data in cluster analysis - Categorization of major clustering methods - Partitioning methods - Hierarchical Methods
pply Chain Management - Legal and Ethical issues - Case studies.