ICS 426: Data Warehousing And Data Mining

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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
Prerequisites
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: 
ICS 324: Database Systems
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.

Textbook(s): 

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​