|
ISQS 3358, Spring 2008 Business
Intelligence Focuses: Dimensional modeling, Data warehousing,
ETL, OLAP, Data processing for analytic tasks Class
meetings MW 2:00-3:20p, Lab 154 Instructor:
Zhangxi Lin, Ph.D., BA708, (806) 742-1926 Office
hours: MW 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 |
Job search | Notes | Your records | Signup | Modify | Student
List | Group
Sign up | Group
List |
|
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 cases. Learning
objectives:
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: 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 Optional textbook: The
Microsoft Data Warehouse Toolkit, Joy Mundy
and Warren Thornthwaite, Wiley, 2006, ISBN
0-471-26715-5 Data Preparation
for Analytics Using SAS, Gerhard Svolba, SAS Press Series, ISBN 978-1-59994-047-2 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 12-15 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 400 points for ISQS 3358 students, or 440 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” |