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ISQS 6339, Fall 2008 Data
Management and Business Intelligence Focuses: Dimensional modeling, Data warehousing,
ETL, OLAP, Data processing for analytic tasks Class
meetings TR 2:00-3:20p, Lab 363 Instructor:
Office
hours: TR 9:00-11:00a Email:
zhangxi.lin@ttu.edu, (This syllabus is subject to further
modification) Home | Schedule | Projects | Job search | Notes
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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 cases. 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 Required
textbook: Delivering
Business Intelligence with Microsoft SQL Server 2005, Publisher:
McGraw-Hill Osborne Media; 1 edition ( Optional textbook: The
Microsoft Data Warehouse Toolkit, Joy Mundy
and Warren Thornthwaite, Wiley, 2006, ISBN
0-471-26715-5 SQL
Server 2005 Integration Services, McGraw Hill Osborne, 2007, ISBN
0072263199 / 9780072263190 Project and the
project group: A data warehousing project will be
accomplished by each team composed of up to two students. 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 500 points Extra
bonus credit: up to 40 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% University Policies Requirements:
Please
contact me if you have any special requirements, or if I need to make special
accommodations for you during the semester. I encourage you to visit
with me about your progress in the course at any time. Integrity. Academic
dishonesty will not be tolerated. All students are required to adhere to
the Texas Tech University Policy on Academic Honesty. Civility in the Classroom. “Students are expected to assist in maintaining a classroom
environment which is conducive to learning. In order to assure that all
students have an opportunity to gain from time spent in class, unless
otherwise approved by the instructor, students are prohibited from using
cellular phones or beepers, eating or drinking in class, making offensive
remarks, reading newspapers, sleeping or engaging in any other form of distraction.
Inappropriate behavior in the classroom shall result in, minimally, a request
to leave class.”
ADA Requirements. Classroom
accommodations will be made for students with disabilities, if requested. Religious Holidays. A student
who intends to observe a religious holy day should make that intention known
to the instructor prior to an absence. A student who is absent from classes
for the observance of a religious holy day shall be allowed to take an
examination or complete an assignment scheduled for that day within a
reasonable time after the absence. 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,
-
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” |