King Fahd University of Petroleum and Minerals

Department of Information and Computer Science

1st Semester 2003-2004 (031)

ICS 490 Data Warehousing and Data Mining (2-3-3)

(Sections 01)

 

1.     Instructor

      Name                     Ejaz Ahmed

      E-mail                    eahmed@ccse.kfupm.edu.sa

      Office                    22 – 124-6

      Phone                    1141 (248-ITC Building-14)

                                   Class    ICS490-01 Data Warehousing and Data Mining

                                   SUN, TUE (11:00am – 11:50am) (24/158)

                                   MON (2:10pm – 5:10pm) Lab 23/015

2. Course

      Course Objectives

·         To understand the basic concepts of Data Warehouse and Data Mining.

·         To understand Data Warehouse tools and technologies

·         Processing and evaluating existing Data Models

·         Introduction to OLAP and Data Mining

·         Data Loading, Data Cleansing and Data Formatting

      Catalog Description

Data Warehousing Concepts and OLAP, Data Warehouse Design and Development, OLAP Technology for Data Mining. Data Mining: Primitive, Languages and Application Developments

      Prerequisite: ICS-334 Database Systems, Programming using Java

      Textbook

Recommended:

“Data Mining Concepts and Techniques” by Jiawei Han and Micheline Kamber, Morgan Kaufmann Publisher, 2001; ISBN: 0-55860-489-8.

 

Selected Research Papers and prepared notes are also included for this course

      Grading

            Quizzes/HW   ----------------------- 10 %

            Exam I           ------------------------ 15 %            (16-MAR-2004: TUE 6:00pm-8:00pm, 14/108)

            Exam II          ------------------------ 15 %           (20-APR-2004: TUE 8:00pm-9:30pm)

            Final Exam    ------------------------ 30 % (Total: 70, plus 30 Lab work)

Course Outline

 

S#

Topic

Chapter

# Of Lectures/ Date Starting

Exam

Quiz

HW

1

Evaluation & Introduction to Data Warehouse*

[2, Notes-1]

3 (15-FEB-2004)

1, F

1

 

2

Data Warehouse Architecture*

[2]

4 (24-FEB-2004)

1, F

1

 

3

Data Warehouse Model and Technology

[Notes-2]

3 (14-MAR-2004)

1, F

1

 

4

External/ Unstructured Data and the Data Warehouse/ Data Migration*

[3, Notes-3, RP]

4 (23-MAR-2004)  

2, F

2

1

5

Introduction to Data Mining

[1]

2 (07-APR-2004) 

2, F

2

1

6

Processing and Evaluating Data Models for Data Mining*

[Notes-4]

3 (13-APR-2004)    

2, F

3

2

8

Data Mining Primitive, languages and System Architecture

[4, 5]

3 (25-APR-2004)

F

4

3

9

Data Mining Association Rules in Large Databases, Decision Trees and Decision rules

[6]

6 (04-MAY-2004)

F

4

3

10

Misc. Topics

 

2 (18-MAY-2004)

F

 

 

*Copy of extra notes and helping material can be obtained from Building 21 floor-2, photocopying center

 

3. General Policies

      Attendance

·         Regular attendance is the university requirement. Attendance will be taken in the beginning of every class.

·         Whenever the number of unexcused absences exceeds 20% of the held classes, the grade DN will be reported without any formal warning.

·         Final exam will be selective comprehensive.

 

      Home Work Submission

·         The home work can be submitted in a class on the due date.

·         Any late submission will not be accepted.

 

      Class Discussion

·         Participation in class discussion is very much encouraged. Asking questions during lectures helps both the instructor and the student. The instructor gets the feedback and the students get the point clarified.

 

      Grading Issues

·         All the grading issues must be resolved within a week after the return of graded material.

·         Exam grades will be submitted a week after the exam date.

·         The best 3 out of 4 quizzes will be considered in the final grade.

     

      Make Ups

·          No make up exams will be given.

     

      Software Applications’ Standards

·          Oracle 8i/ 9i, MS Access, MS SQL & Oracle SQL standards (ANSI standards)