MASTER II International Management
Academic Year 2013-2014
Class Syllabus
Instructor: Dr. Chang Liu
Title: Professor of Management Information Systems and Department Chair
Class: Business Intelligence
Length: Monday, March 3, 2014 to Friday, March 7, 2014 (20 contact hours)
COURSE OBJECTIVES:
This course deals with big data issues and integrating development tools and technologies to
design and implement business intelligence (BI) applications. The students will work with some
popular business intelligence tools such as SAP Business Object Analysis, Microsoft
SQL Server Business Intelligence Studio, and Microsoft Excel to design and implement business
intelligence solutions. Managerial issues related to planning, design, and application of business
intelligence will also be discussed.
LEARNING OBJECTIVES:
Upon completion of the course the student should be able to:
 Understand big data issue and business intelligence
 Understand business impacts and technologies in business intelligence
 Apply Microsoft Excel/SAP tools to analyse data
 Apply Microsoft SQL Business Intelligence Tools to analyse data
 Understand basic business data ming techniques
COURSE DESCRIPTION:
The amount of enterprise data being generated is skyrocketing, and companies are being
challenged to deliver information expediently, pervasively, and efficiently. Business
Intelligence enables business users to make better and faster decisions based on enterprise
data. The course will provide a foundation in the area of business intelligence (BI), including
topics of the business impacts, technologies, and management and development of BI.
Students will also be introduced to various BI technologies such as Microsoft SQL Server
Business Intelligence Studios, SAP Business Object, and Microsoft Excel for analyzing
enterprise data.
TEACHING METHODOLOGY:
Lecture, Class Demonstration, Class Discussion, Hands-on exercises, Small Group Exercises,
and Short Business Cases.
DETAILED OUTLINE
Day
Monday
Tuesday
Wednesday
Thursday
Friday
AM
Course Introduction
Big Data Issues
 BI Applications
 BI Challenges
 Data Warehouse
 BI Tools
9h00 – 12h00
Data Analysis (2)
 Excel Pivot Table
 SAP BusinessObject
 Case Study (1)
 In-class Exercises
PM
13h00 – 17h00
Data Analysis (1)
 Dimensional Modeling
 Business Case
 In-class Exercises
14h00 – 17h00



Excel PowerPivot
Case Study (2)
In-class Exercises
9h00 – 12h00
Data Mining (1)
 Business Case
 Decision Tree
 In-class Exercises
14h00 – 16h00
9h00 – 12h00
Data Mining (2)
 Business Case
 Association Analysis
 In-class Exercises
14h00 – 17h00
10h00 – 12h00
Final Exam
GRADING
Description
Points
Final Exam
50
In-Class Assignements
50
Participation
100
Total 200
ATTENDANCE & PARTICIPATION
All students are expected to attend class and take an active part in all class discussions.
Your participation grade will be based on attendance, as well as my evaluation of your
contribution to the class experience.
Grade My Criteria for Participation
0
 Absent
1
 Present, not disruptive.
2
 Tries to respond when called on but does not offer much.
 Demonstrates very infrequent involvement in discussion/activities.
3
 Demonstrates consistent ongoing involvement with class activities.