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 ICS 426: Data Warehousing And Data Mining

​Course Information

Class/Laboratory Schedule: 

Three 50 minutes lectures per week (3-0-3)

Designation:   Elective Course

Course Level:   Undergraduate


Prerequisite(s) by Topic: 

  • Data preprocessing
  • Data warehouse: data model, design and implementation
  • Data cube: storage, indexing, design, implementation and efficient computation
  • OLAP operators
  • Data mining: Association, classification, clustering, and outlier detection

Prerequisite Courses: 

Catalog Description: 

Review of relational databases and Conjunctive queries, Data Warehousing Concepts and OLAP, Data Warehouse Design and Development, Information and data Integration, OLAP Technology for Data Mining. Data Mining: Primitive, Languages and Application Developments.


Data Mining Concepts and Techniques, 2nd Edition. Jiawei Han and Micheline Kamber, Morgan Kaufmann Publisher, 2005.

Course Outcomes: 

After completion of this course, the student shall be able to:

  • Understand different methods of preprocessing data.
  • Design and implement a simple data warehouse.
  • Design and implement simple data cubes and OLAP operations.
  • Understand the main concepts of data mining.

Topics Covered: 

  • Data preprocessing:
  • Cleaning
  • Transformation
  • Integration
  • reduction
  • Data warehousing Model
  • Design
  • Implementation
  • Data cube:
  • storage
  • indexing
  • design
  • Implementation
  • Efficient computation​