MGT 4020 - Business Intelligence

Fall Semester 2021

 

Course:    MGT 4020 - Business Intelligence
Classroom:  Aderhold Learning Center 202
Instructor:  Steve S. Wong
Phone:  

(678) 467-8199

Office Hours: By appointment
E-Mail:

steve@wongsteve.com

Please add MGT 4020 to the beginning of the subject line.

URL:    wongsteve.com

 

               

 

Prerequisite

 

Text

 

Grading   

 

  MGT 4020 Participation & Homework Projects Exam
  Class Participation 5%    
         
Project 1 Microsoft Excel (Individual)   10%  
         
Project 2 Big Data (Group)   10%  
         
Project 3 Microsoft Access (Individual)   15%  
         
Project 4 SQL (Individual)   15%  
         
Project 5 Minitab (Group)   15%  
         
  Final Exam     30%
         
  Total 5% 65% 30%

           

Plus/Minus Grading Policy

 

 

Course Objective

The objective of the Business Intelligence course it to have the student:

iCollege Skills

You are expected to be proficient in the use of iCollege and all the assignments need to be submitted via the Assignment (i.e. DropBox) in iCollege. Specifically, you should be able to read, upload, and download files; read and send e-mail messages, read and post messages on discussion boards. You are also expected to check the section site daily for any changes, updates, and announcements. A knowledge of these applications is a prerequisite for any course offered by RCB.  The University offers remedial courses in any of these applications.

 

Attendance

Class attendance is expected and necessary component of class participation. In the event that you must miss class, you are still responsible for material covered, and should make arrangements with fellow classmates to remain current with the class. Assignments remain due on the designated date regardless of class attendance. This is a project-oriented class using various computer application programs which require some time commitment. More than 3 missed class periods will result in your class participation marked down one grade. Additional absences may result in a WF.

Class Participation

The emphasis here is to improve your verbal communication skills as well as learn through group discussion. Active class participation is encouraged and your contributions to class discussions will positively impact this portion of your grade.  Class discussions and attendance are included in class participation. I expect constructive contribution to the class discussion on a regular basis.

 

Diversity & Inclusivity

Students in this class are encouraged to speak up and participate during class meetings and online class discussions. The students on our class represent a diversity of individual beliefs, backgrounds, and experiences, and therefore, every member of this class must show respect for every other member of this class.

 

Access & Accommodation

The instructor desires to accommodate students with specific access needs as described in the university policies: https://access.gsu.edu/about-us/ 

 

Honor Code:

Unauthorized Public Posting and Distribution. GSU Policy Prohibiting Students from Posting Instructor-Generated Materials on External Sites. The selling, sharing, publishing, presenting, or distributing of instructor-prepared course lecture notes, videos, audio recordings, or any other instructor-produced materials from any course for any commercial purpose is strictly prohibited unless explicit written permission is granted in advance by the course instructor. This includes posting any materials on websites such as Chegg, Course Hero, OneClass, Stuvia, StuDocu and other similar sites. Unauthorized sale or commercial distribution of such material is a violation of the instructor’s intellectual property and the privacy rights of students attending the class, and is prohibited.

 

Plagiarism or Cheating in any form is not acceptable. While discussion with classmates regarding homework and projects is encouraged, any work submitted must be your own (except, of course, for group projects). Copying any portion of someone else’s assignment is specifically prohibited. Copying or paraphrasing any portion of someone else’s work without proper attribution in a research paper is also specifically prohibited. Evidence of plagiarism or copying on an assignment/exam will result in a grade of zero for that assignment/exam. Please refer to this web page for additional information: https://deanofstudents.gsu.edu/files/2019/07/Academic-Honesty-Policy.pdf.

 

Unauthorized Collaboration is not allowed. Unauthorized collaboration means working with someone or getting assistance from someone (a classmate, friend, etc.) without specific permission from the instructor on any assignment (e.g., exam, paper, homework) that is turned in for a grade. It is also a violation of academic honesty to knowingly provide such assistance to another student. Collaborative work specifically authorized by a faculty member is allowed.

 

We will be following the university's academic honesty policy provided at (among other sources): https://codeofconduct.gsu.edu/

 

Examination:

Exam will be administered in class according to the attached schedule. Exam may be a mixture of short questions, multiple choice and true/false. The exam will test both your understanding of concepts and problem solving ability, and will also include questions about the use of business intelligence applications to solve problems in this course.