Course Expectations and Tentative Syllabus

 

CIS:624                                 Data Warehousing                                                                                 Fall 2002

                                                Bucks County Campus  Room TBD                                            Thr  6:15-9:00pm

 

Professor:              Dr. Michael Redmond    

                                      330 Olney Hall  (215) 951-1096

                                      redmond@lasalle.edu

                                 http://www.lasalle.edu/~redmond/624

 

Office Hours: Thr  5:00-6:00pm

                          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, and costs of realistic tools, there should 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%

 

   Grade Scale:

                A                92-100

A-                 90-91

B+                88-89

B                82-87

B-                80-81

C                60-79

F                < 60

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 29                     Intro to Class,

                                     Basic Elements of Data Warehouse                           Chapt 1

                                     A Sample OLAP based Application

 

Sept 5                     Data Warehouse Lifecycle                                                    Chapt 2

 

Sept 12                      Project Planning and Management                         Chapt 3     

 

Sept 19                   Requirements Analysis                                         Chapt 4

 

Sept 26                   Dimensional Modeling                                      Chapt 5

 

Oct 3                       Dimensional Modeling                                      Chapt 5

 

Oct 10                     Dimensional Modeling                                      Chapt 7

 

Oct 17                     MIDTERM                                                           

 

Oct 24                     Data Warehouse Architecture                          Chapt 8

                                Back Room                                                      Chapt 9

 

Oct 31                     Back Room                                                      Chapt 14

 

Nov 7                     Back Room                                                      Chapt 16

 

Nov 14                   Front Room                                                      Chapt 10, Chapt 17                                                         

 

Nov 21                   OLAP Software                                                               

 

Nov 28   NO CLASS – THANKSGIVING BREAK

 

Dec 5                      Data Mining                                                   supplemental

 

Dec 12                    Final Exam