1. Instructor information
:
Instructor name: Email:
Phone: Cell phone:
Office: Office hours:
2. Class room
:
Main class room (campus):
Online classroom (website):
Class meeting time: weekly
Library hours (where): Fri 8:00- 10:00, VNU-Library.
3. Course information
:
Credit: 4
Course objectives:
The purpose of this course is to focus on the applications of business intelligence and data mining techniques to support the decision making process of
modern enterprises. Coverage includes decision support framework and the roles of business intelligence and data mining, the design and development of
enterprise data warehouse, the role of Business Analytics (BA), and the use of OLAP and multidimensionality in business intelligence. The course also
covers topics related to data mining process, usage of statistical and artificial intelligence techniques in data mining, and the use of dashboards for
comprehensive visualization of enterprise data.
Prerequisite: MSIS 2103.
4. Book and materials
:
Required textbook:
Decision support systems for business intelligence, Vicki L. Sauter, Published by John Wiley & Sons, Inc., Hoboken, New Jersey. 2010
Decision Support and Business Intelligence Systems by Efraim Turban et al.; 8th edition. Pearson Prentice Hall-2008;
Other materials:
Course website:
5. Course requirements
:
Assignments: Exercises are in corresponding sections of the required book.
Computer-based training and testing:
Projects or Team Class Projects: Projects are given by the instructor after finishing a chapter.
Midterm Examinations:
Class attendance/participation: Evaluated by checking in the Attendance Book
Final Examination: Students are directly tested and automatically marked on computers.
6. Grading Procedures
:
Assignments: ............................................................................... 20%
Quizzes: ...............................................................................................
Computer-based training and testing: ..................................................
Projects or Team Class Projects: ................................................... 10%
Midterm Examinations: ............................................................... 25%
Class attendance/participation: ...................................................... 5%
Final Examination: ....................................................................... 40%
Total point and Grades
:
90-100: Good (A) 80-89: Well (B) 70-79: Mean (C)
60-69: Weak (D) 50-59: bad (E) 1-49: too bad (F)
7. Academic integrity Policies
:
- Student may not be absence in 4 sessions. If so, he/she will be prohibitted from test or exam
- Student may not use Vietnamese languague in their class, or will be reduced 2% final marks
- Be punctual to come and leave the class.
- Maximum camncellation time per semester is 6 hours per class.
8. Course outline
:
Upon completion of this course, students should be able to:
1. Critically appraise the role of Decision Support Systems and Business Intelligence in supporting modern enterprises.
2. Design enterprise data warehouse architecture and the ETL process.
3. Apply Business Analytics, OLAP and Multidimensionality for enterprise business intelligence
4. Apply the data mining process in various enterprise-related scenarios
5. Apply statistical and artificial intelligence techniques to data mining
|
Week |
Topic |
Assessment |
Assignment/ Reading |
|
1 |
Introduction to Business Intelligence |
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|
2 |
Decision-Making Systems, Models, and Support |
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|
3 |
Decision Support Systems: An Overview |
Project distribution |
|
|
4 |
Modeling and Analysis |
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|
5 |
Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization |
Assignment distribution |
|
|
6 |
Decision Support System Development |
||
|
7 |
Collaborative Computing Technologies: Group Support Systems |
Midterm |
|
|
8 |
Enterprise Information Systems |
||
|
9 |
Knowledge Management |
Project Submission |
|
|
10 |
Intelligent Decision Support Systems |
Assignment Submission |
|
|
11 |
Knowledge Acquisition, Representation, and Reasoning |
||
|
12 |
Final exam |
Final exam |
9. Comments and notes
:
Make-up: Make-up classes are officially accepted after the Make-up forms are signed by all of the students in the class and directly send to the
Registrars.
Preparation for Class: It is expected that the students read related chapter in textbook and lecture noted before each class. This will help to
capture the topics presented and discussed during class hours.
Use of Class Time: Class time will be used mainly for lectures and discussions. A small part of class hours is used for testing. House works will
be discussed on individual basis.
Class Attendance: Due to the broad range of topics discussed throughout the course and their inter-relationship, it is requested that the students
should attend the class regularly.
Incomplete Grade: A grade of “I” (Incomplete) will be administered only under extreme, verifiable “emergency” situation where the student is
unable to complete some portion of the course work due to circumstances beyond his/her control PROVIDED THE STUDENT IS PASSING THE COURSE.
Assignment Requirement: Assignments of each session must be submited by email before the next session begins.
Instructor’s Signature
Assoc. Prof. Dr. Do Phuc