Units / ITO5202
ITO5202 · 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.
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Monash Online | Teaching period 3 | Monash Online (MO) |
Assessment
The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Assignment 1: Large-Scale Data Processing | Project | 40% | — |
| 2 | Assignment 2: Machine Learning and Streaming Analytics | Project | 50% | — |
| 3 | Final Quiz | Quiz / Test | 10% | — |
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;
- use and evaluate streaming methods in big data processing;
- use big data streaming technologies.
Workload
A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.
| Activity | Duration |
|---|---|
| Workshops | 12 hours |
Ask about ITO5202
Answered from the Handbook fields above — no AI, no guessing. Every answer links back to the source.
Community discussions about ITO5202
CommunityStudent experience, not official rules. Nothing here changes what the Handbook says.