ISQS 3358, Spring 2007

 

Business Intelligence

 

Class meetings (starting on March 5, 2007): MWF 9-10:50a, BA255 or Lab BA 363

Instructor: Zhangxi Lin, Ph.D., BA708, (806) 742-1926

Office hours: M, WR 1:30-3:30p

Email: zhangxi.lin@ttu.edu, MSN: zhangxi.lin@hotmail.com, Google talk ID: zhangxi.lin

 

(This syllabus is subject to further modification)

 

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Course description:

 

Business Intelligence describes the basic architectural components of a business information management environment, ranging from traditional topics such as business process modeling, data modeling, and more modern topics such as business rule systems, data profiling, information compliance and data quality, data warehousing, and data mining. To meet ever increasing demand from BI market this course emphasizes on the skills of business intelligence and be conducted with a series of hands-on cases. This course progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the business intelligence project management.  The students will be asked to carry out a number of SAS projects designed for solving BI problems. The objectives of this course are 1) students will know the best practices and the general principle of BI from these practices; and 2) be able to apply tools, methods, and processes to transform an organization's data into actionable knowledge.

 

Teaching style: Case-based hands-on learning process.

Software tools to be used: SAS Enterprise Guide V4.1, SAS Enterprise Miner 4.3, MS Excel/Access

 

Required textbook:

 

  • Business Intelligence: The Savvy Manager's Guide; Morgan Kaufmann (June 2003); ISBN: 155860916

 

Projects and the project group:

 

Five BI projects will be done by groups through this semester. Each group consists of 2-3 students, but students are allowed to complete the projects alone without based on a group.

 

References:

 

  • Data Mining, Roiger and Gertz. 3rd edition. Addison Wesley, ISBN 0201741288 (This book comes with a Microsoft Excel based data miner called iData Analyzer).
  • Introduction to Data Mining - Using SAS Enterprise Miner, Patricia B. Cerrito, SAS Publishing, ISBN: 978-1-59047-829-5 (http://support.sas.com/pubs)
  • Querying and Reporting Using SAS® Enterprise Guide, SAS Course Notes
  • Getting Started with SAS Enterprise Miner, (Downloadable SAS material)

 

In-class Exercises:

 

There are 10-12 exercises scheduled about two for each week starting from March 19. Exercises could be one to two short answer questions or BI computing assignments. All are open-book and open notes. Most of the exercises will be handed in for grading. The total credit for these exercises is 100 points.  

 

Grading:

 

Five BI projects 200 points (40%)

Lab Assignments 100 points (20%)

Five out of six quizzes (one of them will be dropped whichever with the lowest score) 100 points (20%)

Open book final exam 100 point (20%)

The above are 500 points in total (100%)

 

Bonus credit (up to 25 points or 5%) will be granted in terms of class participation, class involvement, and contributions to the class.

 

A – 90% or higher

B – 80-89.9%

C – 70 – 79.9%

D – 60 – 69.9%

F < 60%

Note: Search on monster.com you can see the number of available BI job positions is “> 5000”