This document outlines the course details for a 20-session Business Intelligence course. The objectives are to learn the concepts and techniques of data warehousing, data mining, and business intelligence. The pedagogy will combine lectures, case analyses, discussion groups, and presentations. Students will be evaluated through class participation, individual assessments like tests and mini-cases, and group work. The course will cover topics like data warehousing concepts and goals, online analytical processing, data marts, data mining processes and algorithms, business intelligence essentials and applications. Reference materials include books and electronic databases. Students will be evaluated internally through activities, a case study, attendance and presentation. An end-term examination will also be given, with the total

1. For Private circulation only
PGDBM Batch 2011­2013
Trimester IV
Business Intelligence
Faculty:
Prof. Kalpana S Kumaran
Institute for Technology & Management
Kharghar
Navi Mumbai

2. Course Title : Business Intelligence
Duration : 20 sessions
Objectives :
To learn the concepts and techniques of data warehousing, data mining & business
intelligence at an introductory level, benefits and applications.
Pedagogy:
The approach to the course will be a combination of lectures, case analyses, discussion
groups, and presentations.
All students are expected to come to class prepared to participate in the day’s activities.
You are expected to review the assigned readings before coming to class and to prepare
thoroughly the case before class. You may be called upon to start the discussion on any
day.
Class Participation & individual assessment: Class participation grades will be based on
the quality of your participation, not just the quantity. Individual assessment would be in
the form of test & mini cases. This gives you an opportunity to use all the analytic and
theoretical skills you absorb throughout the course. Because an important part of
managerial work is making decisions under resource constraints, you can anticipate that
you may not have enough time to complete all the analysis you would like to. All
students are expected to write all examinations.
Group work: Group work will be conducted in class. The Groups must read the case and
come prepared to class. Questions will be given in class and the group must complete
and submit their answers within the group work session.
Contents :­­
Sr. No. Topics Duration Session
in mins
1 What is Data Warehousing? 320 1,2,3 &4
Data Warehousing Concepts
Characteristics of a Data Warehouse
Data Warehouse: Goals and Objectives
Benefits of Data Warehousing
2 On Line Analytical Processing,Data Marts, 80 5

3. Sr. No. Topics Duration Session
in mins
Methodology for Data Warehousing
3 System process and process architecture. 80 6
4 Explanation of Star and Snowflake Schema, 7&8
Metadata &Data Warehouse Model 160
5 Data Mining Introduction
Data Mining Process
Standalone Data Mines 160 9&10
6 Data Mining Algorithms 160 11&12
7 Essentials of Business Intelligence 80 13
8 Business Intelligence Application 80 14
Data warehousing, Mining Case studies 15,16,17 &
9 320 18
11 Business Intelligence Case Studies: 160 19 & 20
Reference Books
1. Data Warehousing Data Mining, & OLAP
Alex Berson
Stephen J. Smith
2. Special Introductory Session: The Essentials of Business Intelligence
3. Data Mining for Business Intelligence
4. Data Warehousing
Amitesh Sinha
5. Data Warehousing – OLAP and Data Mining
S.Nagabhushana
6. Data Mining and Warehousing
S. Prabhu N. Venkatesan
7. Data Warehousing – in the real world
Sam Anahory, Dennis Murray
Electronic DataBase :­­ Ebsco, ProQuest
Internal evaluation
1) mcq,quiz, class activities

4. 2) case study,attendance
3) presentation
Total 40 marks
Examination
End­term 60 marks