BCIS 3610 and ACCT 2030 with grades of C or better; CSCIS 1110 or equivalent (BCIS 2610); MCCI 3710 or 3870; 2.5 GPA. Grades of C or better in each previously taken BCIS and MSCI course, or consent of department.

COURSE DESCRIPTION & PURPOSE

This course investigates model-based approaches to the design of decision systems for business and industry. This includes exploring techniques for data management such as data warehousing, data mining, and data visualization for decision-making in management, management science and accounting. Emphasis will be placed upon data mining techniques for financial auditing. This course is intended for Accounting majors.

GRADING [Approximate points]

Quizzes	7%	35 points
Midterm Exam	24%	120 points
Final Examination	24%	120 points
Projects and Homework	45%	225 points
Totals	100%	500 points

Generally course grades will be posted via WebCT or my website (see below). Incomplete grades will not be given. Final course grades will be based on total points accumulated and the subject judgment of by the instructor of your performance in this class. Final grades will not be posted. Please send Dr. Becker an e-mail at becker@unt.edu if you wish to receive information regarding your final grade.

COURSE DATASETS

Several course datasets (Premiere Products and Henry Books) may be found at:

http://www.coba.unt.edu/itds/faculty/becker/bcis4660/

We will also be using several datasets on the Teradata University website. www.TeradataStudentNetwork.com Use password SPARTANS

COURSE PROCEDURES AND REQUIREMENTS

Subject Matter

The content of this course will be found in selected chapters in the required texts, lectures, notes, Power Point presentations, assigned readings, WebCT forums and the application of various software packages.

You will find much of this subject matter posted via WebCT http://webctvista.unt.edu/ . Some of the content is published in .doc (Word) or .pdf (Adobe) format. If you are working at home and do not have Adobe Acrobat on your machine you may download it from: http://www.adobe.com/products/acrobat/readstep.html

Class Participation

Oral reports, class discussion, topic reports, summarized articles, etc.

Examinations

The exams will be closed-book. Quizzes will be open or closed book at the instructor’s discretion. Early or late final exams will not be given. Late quizzes will not be given. Make-up exams will not be given. Final examination will be comprehensive of all subject matter.

Homework, Projects, and/or Assignments

Problems, cases, and readings will be assigned to support and supplement course subject matter. Each assignment which you turn in must have a separate cover sheet when submitted. This cover page must contain the following information which is typed and centered on the page - your name (Last Name First), the assignment number, the due date for the assignment, the topic of the assignment, Text Title (if any), Chapter (if any) and page number (if any), place a computer generated date stamp on all computer output. Late or early assignments will not be accepted. All assignments are due at the beginning of class on the date due.

All assignments must reflect your original work. Team assignments will include a team member evaluation sheet, which each team member must complete.

Disability Accommodation

The College of Business Administration complies with the American with Disabilities Acts in making reasonable accommodation for qualified students with disability. If you have an established disability as defined in the Americans with Disabilities Act and would like to request accommodation from the Disability Accommodation Office, Union Building.

Attendance

Regular and punctual attendance is essential for this course. While attendance will not be taken, Pop quizzes will be given throughout the semester. If you are not present, you cannot retake the quiz.

Missed Classes

The student is responsible for obtaining material, which has been distributed in class including assignments and assigned readings. Make a friend in the class and use him/her as your source for missed materials. Generally extra copies of handouts will be placed in my course cabinet outside my office.

Course Communications

All students will use BULK MAIL Email all communication with Dr. Becker or questions about class or assignments. Access your Email regularly--at least once each week. You may use my personal Email: becker@unt.edu for course questions. Be sure to put BCIS 4660 in the Subject line.

ETHICAL BEHAVIOR IN BCIS CLASSES

The ITDS Department expects its students to behave at all times in an ethical and legal manner. There are at least two reasons for this. First, ethical behavior affirms the personal value and worth of the individual. Second, both IT and Decision Science professionals frequently handle confidential information on behalf of their employers and clients. Thus employers of BCIS and DSCI graduates expect ethical conduct from their employees because that behavior is crucial to the success of the organization.

Academic dishonesty is a major violation of ethical and legal behavior. The ITDS Department defines academic dishonesty as claiming the work of others as your own, or using illegal or unapproved means to raise your grade in a class. Examples include: copying answers from another person’s paper; using unapproved notes during an exam; copying computer code from another person’s work; having someone else complete your assignments or take tests on your behalf; stealing code printouts, software, or exams; recycling assignments submitted by others in prior or current semesters as your own; and copying the words or ideas of others from books, articles, reports, presentations, etc. for use as your own thoughts without proper attribution (i.e., plagiarism). It does not matter whether you received permission from the owner of the copied work; claiming the material as your own is still academic dishonesty.

The ITDS Department believes it is very important to protect honest students from unfair competition with anyone trying to gain an advantage through academic dishonesty. Consequently, there will be in-class testing to validate all major assignments you complete out of class. This may be accomplished by examination, oral reports, individual interviews or any other means your professor may deem appropriate. You must pass these validation tests with a grade of “C” or better to have your out-of-class work count in your term grade. Further, the student grade for academic dishonesty in BCIS classes is an immediate “F” for the course involved and referral of the case to the COBA Academic Advising Office.

By my signature below, I attest that I understand the above policy. I will behave ethically in this class, and will encourage my classmates to behave ethically. I also understand that I have a moral responsibility to report to my instructor any suspected case of academic dishonesty in this class.

_____________________________________________________

Print your name and give your signature.

___________________________ _______/______/2008

Student ID number Today’s date

My course scores my be published using the last 5 digits of my student number

(SN) __ __ __ __ __ ; or the following 5-character (numeric) code: __ __ __ __ __.

If both numbers were left blank, your scores will NOT be published.

This is YOUR COPY. Turn in the one below.

*BCIS 4660 Data Warehousing; Fall 2008*
*CLASS SCHEDULE:* (Subject to change; effective *9/11/2008*)
Week	Date	Topics	Readings	Assn No.**
1.1	Aug 26	Introduction to Data Warehousing & Data Mining	Pratt; Marakas, Adamson Introductions	Pop Quizzes (35 pts)*
1.2	Aug 28	Relational Databases	Pratt 1
2.1	Sep 2	QBE	Pratt 2	Exercise #1 (10)
2.2	Sep 4	QBE	Pratt 2
3.1	Sep 9	SQL	Pratt 3; Appendix C	Exercise #2 (10)
3.2	Sep 11	SQL	Pratt 4; Appendix D
4.1	Sep 16	Normal Forms	Pratt 5	Exercise #3 (20)
4.2	Sep 18	DBMS	Pratt 5
5.1	Sep 23	DBMS	Pratt 6
5.2	Sep 25	Data Warehousing Overview; Dimensional Modeling	Notes; Adamson 1; Marakas 1
6.1	Sep 30	Data Mining, Data Visualization	Continued	Assign #4 (20)
6.2	Oct 2	Fact Tables & Dimension Tables; Retail Sales Models	Adamson 2; Pratt 9; Marakas 1;
7.1	Oct 7	The Data Warehouse; Direct Sales	Adamson 2; Review	Assign #5 (20)
7.2	Oct 9	Review
8	OCT 14	Midterm (Cover thru Class 7.1)		Mid Exam(120)

Week	Date	Topics	Readings	Assn No.**
8.2	Oct 16	Review Midterm; Data Loading Meta Data; Semantic Object Models (SOM)	SOM Tutorial (Notes); Marakas 2
9.1 & 9.2	Oct 21 & 23	Data Modeling; Semantic Object Models (SOM)	Marakas 2; SOM Tutorial (Notes)
10.1	Oct 28	SAS Enterprise Miner; Teradata Data Warehousing; SAS EM	Notes: Data Mining
10.2	Oct 30	SAS Enterprise Miner; Teradata Data Warehousing; SAS EM	Notes: Data Mining;	Assign #6 (20); ERWin/ SOM Diagrams
11.1	Nov 4	Data Visualization; Data Warehousing; Budgets	Marakas 3; Adamson 8
11.2	Nov 6