Course Expectations and Tentative
Syllabus
CIS:624 Data
Warehousing Fall
2001
Olney Room 201 Thr 6:15-9:00pm
Professor: Dr. Michael Redmond
330
Olney Hall (215) 951-1096
http://www.lasalle.edu/~redmond/624
Office Hours: Thr
5:00-6:10pm
And at other times by appointment.
Also, by phone and e-mail.
Text:
Kimball, R., Reeves, L., Ross, M., and
Thornthwaite, W.., The Data Warehouse Lifecycle Toolkit, Third Edition, Wiley,
1998
Course Description:
Data
Warehousing is a popular and growing
area involving the use of large scale data stores to support business
decision-making. This course is intended to introduce the student to the
critical success factors in designing and implementing a data warehouse. The
textbook is geared toward people who will be applying the ideas in their
organization – i.e. it is geared toward the practitioner not the
theoretician. While we are in some ways
limited in our hands-on possibilities due to the size of realistic data, there
will be hands-on opportunities with OLAP software. It is anticipated that we
will do some role-play of situations in order to make other parts of the course
come to life.
Topics
to be covered include management, requirements analysis, design,
infrastructure, data staging, data access, and data mining. Data mining is largely outside of the scope
of the text, so supplemental readings will be identified.
The
course assumes knowledge of database concepts, particularly relational database
concepts. The text assumes some familiarity with client-server ideas (but not
practice).
Grading:
Midterm 25%
Final Exam 40%
Design Assignment 10%
OLAP Assignment 10%
TBD Assignment 10%
Class Participation 5%
Fall
semester 1999 brought the debut of the A, A-, B+, B, B-, C, F grading scheme. I
will assign +’s and –‘s, but the number will probably be small, limited to
people close to grade boundaries.
No
make up exams unless arranged in advance.
Final
exam is cumulative, but will focus more heavily on the (previously untested)
final half of the course.
There
will be several, varied assignments over the course of the semester. One will
involve using Cognos PowerPlay OLAP software. This software is accessible over
the WWW so should be able to be used outside La Salle. A second assignment will
involve designing a hypothetical data mart. The third is still to be
determined. The assignment due dates will be specified when they are assigned.
Course
Objectives
Concepts:
1. The
student should understand the benefits of database warehousing.
2. The
student should understand the basic elements in the data warehouse.
3. The
student should understand the phases in the data warehouse lifecycle.
4. The
student should understand the basic issues in data warehouse project
management.
5. The
student should understand the process of data warehouse requirements analysis.
6. The
student should understand the principles of dimensional modeling using star
schemas.
7. The
student should understand the issues involved in staging data from operational
systems into the data warehouse, including data extraction, transformation,
cleansing, and building aggregates.
8. The
student should understand the issues involved in providing warehoused data to
business users to support decision making.
9. The
student should understand the issues involved in determining infrastructure
needs to support a data warehouse
10. (time
permitting) The student should understand the use of data mining on warehouse
data, and requirements mining puts on the warehouse.
Applications:
1. The
student should gain some exposure and experience with a commercial OLAP tool.
2. The student should gain experience creating
a logical design for a data mart.
3. The
student should learn about the different categories of tools related to data
warehousing currently available.
Tentative
Course Plan:
Date
Material Reading
Aug 30 Intro
to Class,
Basic
Elements of Data Warehouse Chapt 1
A Sample
OLAP based Application
Sept 6 Data
Warehouse Lifecycle Chapt 2
Sept 13 Project
Planning and Management Chapt 3
Sept 20 Requirements
Analysis Chapt
4
Sept 27 Dimensional
Modeling Chapt
5
Oct 4 Dimensional
Modeling Chapt
5
Oct 11 Dimensional
Modeling Chapt
7
Oct 18 MIDTERM
Oct 25 Data
Warehouse Architecture Chapt 8
Back
Room Chapt
9
Nov 1 Back
Room Chapt
14
Nov 8 Back
Room Chapt
16
Nov 15 Front
Room Chapt
10, Chapt 17
Nov 22 NO CLASS – THANKSGIVING BREAK
Nov 29 OLAP
Software
Dec 6 Data
Mining supplemental
Dec 13 Final
Exam