Data Warehousing and Data Mining (CSC-459)

Tribhuvan University

Institute of Science and Technology

Bachelor of Science in Computer Science and Information Technology

8th Semester 
Course Title: Data Warehousing and Data Mining

Course no: CSC-459                                                                  Full Marks: 60+20+20

Credit hours: 3                                                                          Pass Marks: 24+8+8

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:

1. Data Mining Concepts and Techniques, Morgan Kaufmann J. Han, M Kamber
2. 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%