Units / FIT3003
FIT3003 · Business intelligence and data warehousing
2026 Handbook6 credit pointsLevel 3Faculty of Information Technology
Last checked: 23 Aug 2026 UTCOverview
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 resulted in the faster generation of reports and more flexible analysis based on the data repositories. This unit will explore the concepts of data warehousing and OLAP, covering the data processing technological requirements for data warehousing and OLAP and will provide hands on experience on designing data warehousing and OLAP systems.
Areas of study: Business analytics Business information systems Computational science Data science
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Malaysia | Second semester | Teaching activities are on-campus (ON-CAMPUS) |
| Clayton | Second semester | Flexible (FLEXIBLE) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Assessment 1 | Quiz / Test | 10% | Threshold |
| 2 | Assessment 2 | Artefact | 40% | Threshold |
| 3 | Assessment 3 | Quiz / Test | 10% | Threshold |
| 4 | Scheduled final assessment (2 hours and 10 minutes) | Examination | 40% | Threshold |
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 details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
Learning outcomes
- Design multi-dimensional databases and data warehouses;
- Use fact and dimensional modelling;
- Implement online analytical processing (OLAP) queries;
- Explain the roles of data warehousing architecture and the concepts of granularity in data warehousing;
- Create business intelligence reports using data warehouses and OLAP.
Workload
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
| Activity | Duration |
|---|---|
| Seminars | 24 hours |
| Laboratories | 24 hours |
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