CSC-459: Data Warehousing and Data Mining Macro Syllabus

-->

Course Title: Data Warehousing and Data Mining

Course no: CSC-459                                                                          Full Marks: 70+10+20

Credit hours: 3                                                                                    Pass Marks: 28+4+10

Nature of course: Theory (3 Hrs.) + Lab (3 Hrs.)

Course Synopsis:       Analysis of advanced aspect of data warehousing and data mining.

Goals: This course introduces advanced aspects of data warehousing and data mining, encompassing the principles, research results and commercial application of the current technologies

Course Content:

Unit 1.                                                                                                                         5 Hrs.

Review of basic concepts of data warehousing and data mining, reasons for their use and benefits and problems arising

Unit 2.                                                                                                                         5 Hrs.

Data warehouse logical design: star schemas, fact tables, dimensions, other schemas, materialized views

Unit 3.                                                                                                                         5 Hrs.

Data warehouse physical design: hardware and i/o considerations, parallelism, indexes

Unit 4.                                                                                                                        10 Hrs.

Data warehousing technologies and implementations: data extraction, transportation, transformation, loading and refreshing. Data warehouse support in SQL Server 2000 and Oracle 10g

Unit 5.                                                                                                                         8 Hrs.

From data warehousing to data mining: OLAP architectures, design and query processing. SQL extensions for OLAP

Unit 6.                                                                                                                         6 Hrs.

Data mining approaches and methods: concept description, classification, association rules, clustering

Unit 7.                                                                                                                         4 Hrs.

Mining complex types of data

Unit 8.                                                                                                                         5 Hrs.

Research trends in data warehousing and data mining

Laboratory works:      Design and development of data warehousing and data mining tools.

Text Books:               Data Mining Concepts and Techniques, Morgan Kaufmann J. Han, M Kamber

Data Mining with Microsoft SQL Server 2000 C. Seidman

Homework

Assignment:               Assignment should be given throughout the semester.

Computer Usage:       No specific

Prerequisite:               C, Data Structure, Database

Category Content:     Science Aspect:            40%

                                    Design Aspect: 60%