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ISQS 3358, Spring 2009 Business
Intelligence Focuses: Principles of BI, Dimensional modeling,
Data warehousing, ETL, OLAP, Data analysis Class
meetings: MW 2-3:20p, BA 270 (or Lab BA 363) Instructor:
Zhangxi Lin, Ph.D., BA708, (806) 742-1926 Office
hours: MWTr 9:00-11:00a Email:
zhangxi.lin@ttu.edu, MSN: zhangxi.lin@hotmail.com, Google
talk ID: zhangxi.lin (This syllabus is subject to further
modification) Home | Schedule | Projects |
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Course
description: Data
management comprises all the disciplines related to managing data as a
valuable resource. Business intelligence (BI) is referred to as applications and
technologies which are used to gather, provide access to, and analyze data
and information about their company operations. Business intelligence systems
can help companies have a more comprehensive knowledge of the factors
affecting their business, such as metrics on sales, production, internal
operations, and they can help companies to make better business decisions.
This course is to be based on the contents covered by database management to
further train students the skills methodologies, and knowledge how to
accomplish data management tasks with the applications of BI tools and
techniques. The main components of this course include:
The
course is lectured with hands-on exercises. Prerequisites:
Database, statistics Learning
objectives:
Assessment of
Learning:
Teaching style: Case-based
hands-on learning process. Software tools to be used: Microsoft SQL Server 2005, SAS
Enterprise Guide V4.1 Prerequisites: Any database courses Required
textbook: Business
Intelligence, Pearson Prentice Hall, 2008, ISBN-10: 013234761X Efraim Turban, Ramesh Shard,
Jay E. Aronson, David King Optional textbook: Delivering
Business Intelligence with Microsoft SQL Server 2005, Publisher: McGraw-Hill
Osborne Media; 1 edition (January 23, 2006), ISBN-10: 0072260904, ISBN-13:
978-0072260908 The
Microsoft Data Warehouse Toolkit, Joy Mundy
and Warren Thornthwaite, Wiley, 2006, ISBN
0-471-26715-5 Projects and the
project group: Undergraduate Students: need to complete a
BI project by groups through this semester. Each group consists of no more
than 3 students. Graduate Students taking ISQS 3358+ISQS7342
(equivalent to ISQS 6339): Need to accomplish the BI project individually plus
an additional project in SAS data preparation for analytics. In-class
Exercises: There are 12 exercises. Exercises could be one to
two short answer questions or BI computing assignments to be completed in the
class. 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. Students
may be allowed to skip up to two in-class exercises without losing any
credit. Missing any extra exercise will cost 5 points. Students who complete all exercises will
earn a bonus of 5 points. Grading:
The
total is 380 points for ISQS 3358 students, or 420 points for ISQS 7342
students Extra
bonus credit: up to 30 points based on the evaluation of the involvement in
the class activities. A – 90% or higher B – 80-89.9% C – 70 – 79.9% D – 60 – 69.9% F < 60% References:
1.
StatLib: http://lib.stat.cmu.edu/ 2.
MLnet: http://www.mlnet.org/ 3.
KDNuggets: http://www.kdnuggets.com/ 4.
Weka: http://www.cs.waikato.ac.nz/ml/weka/ 5.
Open source
data mining projects: http://www.kdkeys.net/forums/72/ShowForum.aspx 6.
Open source
data mining tools: http://dmoz.org/Computers/Software/Databases/Data_Mining/Public_Domain_Software/ ·
Microsoft SQL
Server Management Studio Express (SSMSE): Download ·
Download
samples and sample databases from the Microsoft Download Center ·
Microsoft BI Cases, SAS Cases ·
BI
Application Case: Playing
by the Numbers: Baseball and BI, By Mel Duvall,
Oct 29, 2007, -
Boston Red Sox World Series win is testament to team's ability to put
business intelligence to work on and off the field. Note: Search
on monster.com you can see the number of available BI job positions is “>
5000” |