Overview
Automation and the use of technological tools have resulted in the accumulation of vast volumes of data by modern business organisations. Data warehouses have been set up as repositories to store this data and improved techniques now result in the speedy collection and integration of such data. OLAP technology has … For more content click the Read More button below.
Offerings
S2-01-CLAYTON-ON-CAMPUS
S2-01-MALAYSIA-ON-CAMPUS
Rules
Enrolment Rule
Contacts
Chief Examiner(s)
Associate Professor David Taniar
Unit Coordinator(s)
Agnes Haryanto
Dr Soon Lay Ki
Learning outcomes
On successful completion of this unit, you should be able to:
1.
Design multi-dimensional databases and data warehouses;
2.
Use fact and dimensional modelling;
3.
Implement online analytical processing (OLAP) queries;
4.
Explain the roles of data warehousing architecture and the concepts of granularity in data warehousing;
5.
Create business intelligence reports using data warehouses and OLAP.
Teaching approach
Active learning
Assessment summary
This unit has threshold mark hurdles. You must achieve at least 45% of the available marks in the final scheduled assessment, at least 45% in total for in-semester assessments, and an overall unit mark of 50% or more to be able to pass the unit. If you do not achieve the threshold mark, you will receive a fail grade (NH) and a maximum mark of 45 for the unit.
Assessment
1 - Take Home Test
2 - Major Assignment
3 - FLUX Participation
4 - Scheduled final assessment (2 hours and 10 minutes)
Scheduled and non-scheduled teaching activities
Laboratories
Lectures
Workload requirements
Workload
Learning resources
Technology resources
Availability in areas of study
Business analytics
Business information systems
Computational science
Data science
Business information systems
Computational science
Data science