ITI5202 Data processing for big data
Faculty of Information Technology
ITI5202 Data processing for big data is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2026. It needs ITI9132 and ITI9136.
- Credit points
- 6
- Offered in 2026
- Other periods
- Indonesia
- Assessment
- Exam 40%
- and 2 other tasks
- Workload
- 144 hours
- per semester
This is the 2026 handbook entry. See the 2027 entry.
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Requisites
Before ITI5202
Prerequisites
Pass these before you enrol.
Prohibitions
You can't enrol if you have passed any of these.
After ITI5202
No unit lists ITI5202 as a prerequisite in the 2026 handbook.
Enrolment rules
This unit is only available to students enrolled at the Indonesia campus.
Equivalent units
The same content under another code. Only one of them counts.
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 in 2026
| Teaching period | Campus | Mode |
|---|---|---|
| Monash Indonesia term 3 | Indonesia | Blended |
Assessment
- Assessment 1: Weekly tasksQuiz / Test10%
- Assessment 2: Group projectProject50%
- Assessment 3: End-of-term QuizExamination40%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
identify and explain big data concepts and technologies;
- 2
write and interpret parallel database processing algorithms and methods;
- 3
apply common data analytics and machine learning algorithms in a big data environment;
- 4
use and evaluate streaming methods in big data processing;
- 5
use big data streaming technologies.
Workload and teaching
- Laboratories24 hours
- Lectures24 hours
- Teaching approachActive learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per teaching period 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 activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.
Learning resources
Recommended resources
- A. Kozlov: Mastering Scala machine learning : advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop, Birmingham, UK : Packt Publishing, 2016
- A. Alexander: Scala cookbook, Beijing : O'Reilly, 2013
- A.S. Tanenbaum, T. Austin: Structured Computer Organization, 6th Ed, Boston : Pearson, 2013
Contacts
- Unit Coordinators
- Professor Taufiq Asyhari
- Chief Examiners
- Associate Professor David Taniar
Common questions
What are the prerequisites for ITI5202?
You need ITI9132 and ITI9136 before you enrol. Enrolment rules also apply.
When is ITI5202 offered?
ITI5202 has no offerings listed in the 2026 handbook.
How much work is ITI5202?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ITI5202 have an exam?
Yes. The exam is worth 40% of the final mark, alongside 2 other tasks.