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General Information
| Computing Information: | http://www.umsl.edu/technology/ | |
| Computer Lab Information: | http://www.umsl.edu/technology/instructionalcomputing/ | |
| Advanced MIS Lab Information: | http://www.umsl.edu/business/mis/MISlab.html | |
| Library Information: | http://www.umsl.edu/services/library/ | |
| Campus Events | http://www.umsl.edu/~sauterv/analysis/event_schedule.html | |
| Acceptable Usage Policy | http://www.umsl.edu/technology/policy/acceptable.html | |
| Student Technology Guide | http://www.umsl.edu/technology/publications/stutechguide/ | |
| Student Conduct Code | http://www.umsl.edu/studentlife/dsa/student_planner/policies/conductcode.html | |
| UMSL Home Page | http://www.umsl.edu/ | |
| IS Home Page | http://mis.umsl.edu |
Online Materials
| Class Web Site | http://www.umsl.edu/~sauter/DSS/6833start.html | |
| DSS Current Page | http://www.umsl.edu/~sauter/DSS/current.html | |
| Readings | http://www.umsl.edu/~sauter/DSS4BI/links.html | |
| Student Information Form | http://www.umsl.edu/~sauter/DSS/student_info.html | |
| Group Evaluation Form | http://www.umsl.edu/~sauter/DSS/group_eval.html |
Prerequisites: LOM 5300: Statistical Analysis
Semester Goals: Decision Support Systems are tools decision makers use to gain a better understanding of their business and customers. They are the "front-end" technology that is generally associated with a data warehouse, and which provides the modeling and analysis capabilities to help decision makers see avenues through which to gain competitive advantage. As the name suggests, a DSS focuses how models, data, and other analytical tools decision makers might use in the reasoned consideration of the options available to them. In the current environment in most businesses, DSS are being implemented as intranets and so require web-based technologies.
This semester, we will consider general topics of DSS design. In addition, we will focus on how DSS can be used to improve organizational excellence, especially as a CRM tool. Thus, projects and papers will have a CRM analytical bent to them.
Assignments: See assignments page.
Exams: There will be a midterm and a final exam.
Make-up exams will be provided only if Dr. Sauter has been notified prior to the exam and if you have an acceptable reason for missing the exam. Under all other circumstances, a grade of zero (0) will be assigned. NO late exams (if it is a take home exam) will be accepted.
Grading Policy: The following proportions will be used for grading.
| Networking Activities | 10% | |
| Analytics Assignment | 15% | |
| Business Intelligence Assignment | 15% | |
| Paper | 20% | |
| Midterm | 20% | |
| Final Exam | 30% | |
Approximate letter grades will be assigned when exams and projects are returned. Students should remember, however, that the term average is a weighted average of the numerical grades, not an average of the approximate letter grades.
Drop Policy: For the purposes of this policy, the "effective drop date" is the date which I am informed of the drop or the actual date of the drop, which ever is later. Students can and may inform me by leaving me a note in my mailbox, leaving me a message (on voice mail or email) or by speaking to me in person or over the telephone.
A student may drop this class until March 19 with a passing grade. (Note the University policy states that you may drop until February 13 without receiving a grade; this policy is simply an extension of the University policy.) Between March 20 and April 7, a student will receive either a passing grade (excused) or a failing grade (F) depending upon his or her performance (current grade) in the course. A student may withdraw after April 7 only with and solely with the approval of the dean of his or her division. If you want to withdraw after this date, go directly to your dean; do not ask for my signature -- my signature is not needed and I will not provide it. Under no circumstance may a student drop this class after May 2, 2012.
Academic Honesty: According to the University Standard of Conduct, Section 6.0101,
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Furthermore, note that the University’s Collected Rules 200.010 B.1 REQUIRE faculty to notify Academic Affairs of suspected cases of dishonesty. It states, “In all cases of academic dishonesty, the instructor shall make an academic judgment about the student’s grade on that work and in that course. The instructor shall report the alleged academic dishonesty to the Primary Administrative Officer.”
For the purposes of this class, cheating will include: plagiarism (using the writings of another without proper citation), copying of another (either current or past student's work), working with another on individually assigned work or exams, unauthorized marking on a graded paper or exam, or in any other way presenting as one's own work that which is not entirely one's own work. It is unacceptable to seek the help of another (whether in the class or not) for help on an exam; this is considered academic dishonesty.
Any student who is caught cheating on any assignment or exam will receive a grade of zero (0) for that assignment or exam. Further, a recommendation will be made to the appropriate university officials that additional disciplinary action be taken.
Disabilities: Please inform me of any physical disabilities that could affect your learning. I am happy to make reasonable accommodations to improve the learning environment, but I need to know about them in order to help. If, during the semester, you are experiencing a serious emotional trauma, please inform me of this before taking an exam; once an exam is taken the grade must be counted and no "retake" is possible.