Business Intelligence

Course Objectives :

1. To understand the basics of business intelligence, business decisions, data warehouses and its architecture, KDD process.
2. To understand the applications of data mining in business, data mining techniques for CRM, text mining and web mining.
3. To acquire knowledge in business intelligence, application in various domains and best practice.
4. To understand the knowledge management, its architecture, approaches and tools.

Course Outcomes (CO)

1. CO 1 - Understand the basics of business intelligence, business decisions, data warehouses and its architecture, KDD process.
2. CO 2 - Understand the applications of data mining in business, data mining techniques for CRM, text mining and web mining.
3. CO 3 - Apply business intelligence in various domains.
4. CO 4 - Understand the knowledge management, its architecture, approaches and tools.

UNIT-I

Introduction to business intelligence and business decisions - Data warehouses and its role in Business Intelligence, Creating a corporate data warehouse, Data Warehousing architecture, OLAP vs. OLTP, ETL process, Tools for Data Warehousing, Data Mining, KDD Process

UNIT-II

Applications of Data Mining in Business - Data Mining Techniques for CRM, Text Mining in BI, Web Mining, Mining e-commerce data, Enterprise Information Management, Executive Information Systems

UNIT-III

Business Intelligence, Function, Process, Services & Tools, Application in different domains, Operational BI, Customizing BI, Managing BI projects vs. Traditional IS projects, Managing BI projects, Best Practices in BI Strategy

UNIT - IV

The ten key principle of KM, Knowledge Management Architecture, Knowledge Management Vs. Knowledge Processing, KM approaches, KM Tools, KM Infrastructure, KM models, KM Strategies

Textbook(s):

1. Business Intelligence in the Digital Economy - Opportunities, Limitations and Risks, M.Raisinghani, Idea Group Publications, 2004
2. Knowledge Management and Business Innovation, Yogesh Malhotra, Idea Group, 2001

References:

1. Introduction to Data Mining and its Applications, Sumathy, Sivanandam, Springer Verlag, 2006