Units / FIT5202
FIT5202 · Data processing for big data
2027 Handbook6 credit pointsLevel 5Faculty of Information Technology
Overview
This unit focuses on big data processing, including volume, complexity, and velocity using the latest big data technologies. In big data volume, it covers large volume data processing using parallel technologies. In large dimensionality (or complexity), it covers various data analytics methods for parallel processing. For the velocity, it covers data streaming processing.
Areas of study: Data science
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | First semester | Teaching activities are on-campus (ON-CAMPUS) |
| Clayton | Second semester | Some activities have a choice of on-campus or online teaching activities (FLEXIBLE) |
| Malaysia | Second semester | Evening (EVENING) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Assignment 1 | Project | 15% | — |
| 2 | Assignment 2 | Project | 30% | — |
| 3 | Quiz | Quiz / Test | 5% | — |
| 4 | Lab tasks | Exercise | 5% | — |
| 5 | Scheduled Final assessment | Examination | 45% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
Learning outcomes
- identify and explain big data concepts and technologies;
- write and interpret parallel database processing algorithms and methods;
- apply common data analytics and machine learning algorithms in a big data environment in a secure and ethical manner;
- use and evaluate streaming methods in big data processing;
- use big data streaming technologies.
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 |
|---|---|
| Laboratories | 24 hours |
| Workshops | 24 hours |
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