• To know how to derive meaning form huge volume of data and information.
• To understand how knowledge discovering process is used in business decision making.
UNIT I INTRODUCTION
Data mining, Text mining, Web mining, Spatial mining, Process mining, BI process- Private and Public intelligence, Strategic assessment of implementing BI.
UNIT II DATA WAREHOUSING
Data ware house – characteristics and view – OLTP and OLAP – Design and development of data warehouse, Meta data models, Extract/ Transform / Load (ETL) design.
UNIT III DATA MINING TOOLS, METHODS AND TECHNIQUES
Regression and correlation; Classification- Decision trees; clustering –Neural networks; Market basket analysis- Association rules-Genetic algorithms and link analysis, Support Vector Machine, Ant Colony Optimization.
UNIT IV MODERN INFORMATION TECHNOLOGY AND ITS BUSINESS OPPORTUNITIES
Business intelligence software, BI on web, Ethical and legal limits, Industrial espionage, modern techniques of crypto analysis, managing and organizing for an effective BI Team.
UNIT V BI AND DATA MINING APPLICATIONS
Applications in various sectors – Retailing, CRM, Banking, Stock Pricing, Production, Crime, Genetics, Medical, Pharmaceutical.
TOTAL: 45 PERIODS
• Big Data Management.
• Appreciate the techniques of knowledge discovery for business applications.