OFFICE HOURS

Tue/Thur: 2:00-3:00 PM & 5:00-6:00 PM; and by appointment

WEB LINKS

http://www.teradata.com/t/page/144826/index.html

COURSE DESCRIPTION & PURPOSE

This course provides an overview of the different components to Business Intelligence. The course is designed to provide a thorough understanding of the business potential of data warehousing, data mining, forecasting, BPM, Predictive Analytics, Analytics, Dashboards & Scorecards, ETL, & CRM. These objectives are met through a combination of class lectures, readings, case studies, and outside speakers.

GRADING [Approximate points]

Quizzes	20%	100 points
Midterm Exam	25%	125 points
Final Examination	25%	125 points
Individual Project	10%	50 points
Team Project: Term Paper	20%	100 points
Totals	100%	500 points

Alignment in the 21^st Century

Individual Project:

Students will need to logon to Teradata Student Network (TSN/TUN )and questions using the SQL statements provided. Students will be given access to the SAMS DB with a Logon/ Password.

Team Project:

Work in teams of 4 to 5. Each team will be assigned a topic or may chose a topic related to the data warehousing and business intelligence trend. The project requires a completion of a 12-15 page Term Paper and a 30-minute presentation of the topic. All Articles, References and Additional materials must be turned in with the Term Paper in a 3-ring Binder.

Examinations

The exams will be closed-book. Early or late final exams 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.

Quizzes

Students will turn in a 1 page summary report each week based on the assigned reading. Students must be prepared to discuss the reading in class the day it is due.

Article Reading Assignments (available on Teradata Student Network):

Week	Due Date	Topics	Article Reading
1		BI	Williams, Steve. “Accessing BI Readiness: A key to BI ROI.”
2		Analytics	Davenport, T.H. “Competing on Analytics.”
3		Predictive Analytics	Krantik Das and G. S. Vidyashankar. “Competitive Advantage in Retail Through Analytics: Developing Insights, Creating Value.”
4		Data Mining	Zaima, Arlene and Kashner, James. “A data mining Primer for the Data Warehouse Professional.”
5		Data Warehouses	Gartner Research. “Key Issues for Data Warehousing, 2007.”
6		CRM	Baseline Insight. “What is CRM?”
7		BPM	Gregory, Marianne A. “Keys to Successful Performance Management: Getting Past the Excitement of Technology to Achieve Results.”
8		Dash Board & Scorecards	Eckerson, Wayne. “The New Face of Business Intelligence: Dashboards and Scorecards.”
9		Forecasting	Gartner Research. “Selecting Analytics Technologies for Sales Organizations.”
10		ETL	Gartner Research. “Who Who in Extraction, Transformation & Loading.”