Courses Catalogue

Data Warehousing

ACADEMIC PROGRAMME: Information Technology, B.Sc
COLLEGE/SCHOOL/FACULTY: School of Mathematics and Computing
PROGRAMME TYPE: Undergraduate

Course Description

Course Description:

The course is majorly lecture based with some laboratory sessions however with no internship required.

Course Objective:

The Objectives of this course are to:

1.         Make students understand the role and operation of data warehouses

2.         Equip students with skills of developing data warehouses

3.         Equip students with skills of maintaining existing data warehouses

4.         Equip students with skills of manipulating data warehouses to generate information for business decision making


Course Learning Outcomes:

1.         After successfully completing this course, students should be able to:

2.         Distinguish between on-line transaction processing (OLTP) and online analytical processing (OLAP), and the relationship between these concepts and business intelligence, data warehousing and data mining

3.         Create a simple data warehouse (“data mart”)

4.         Describe how structured, semi-structured, and unstructured data are all essential elements of enterprise information and knowledge management. In this context, the students will learn the principles of enterprise search

5.         Explain how data warehousing combined with good business intelligence can increase a company’s bottom line

6.         Describe the components of a data warehouse and different forms of business intelligence that can be gleaned from a data warehouse and how that intelligence can be applied toward business decision-making

7.         Develop dimensional models from which key data for critical decision-making can be extracted

8.         Sketch out the process for extracting data from disparate databases and data sources, and then transforming the data for effective integration into a data warehouse

9.         Load extracted and transformed data into the data warehouse

10.       Understand the different kinds of data mining algorithms and how they are applicable in different business case studies.