FIT5148 Big data management and processing
Faculty of Information Technology
FIT5148 Big data management and processing is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology, offered in 2020 in Semester 1 at Malaysia and Monash Online. It needs FIT9132 and (FIT9131, FIT9133 or FIT9136).
- Credit points
- 6
- Offered in 2020
- Semester 1
- Malaysia, Monash Online
- Assessment
- Exam 60%
- and 2 other tasks
- Workload
- 144 hours
- per semester
The 2027 handbook has no page for FIT5148. This is its 2020 entry, the latest one.
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Requisites
Before FIT5148
After FIT5148
No unit lists FIT5148 as a prerequisite in the 2020 handbook.
Enrolment rules
Prerequisite: For students enrolled in E3001, E3002, E3005, E3010, E3011, E3007 completing the Software Engineering specialisation: FIT2099 and FIT3171 Students should have an introductory understanding of database concepts and SQL and some programming background.
Overview
Data engineering is about developing the software (and hardware) infrastructure to support data science. This unit introduces software tools and techniques for data engineering, but not hardware. It will cover:
- introduction to big data processing, covering volume, variety, and velocity;
- large volume data processing using parallel technologies;
- variety data formats, including unstructured and semi-structured data, using NoSQL databases;
- velocity data processing, covering data streaming;
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Malaysia | Evening |
| Teaching period 5 | Monash Online | Mo |
Assessment
- In-semester assessmentThreshold hurdle40%
- Examination (2 hours and 10 minutes)Threshold hurdle60%
- In-semester assessment100%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Identify and assess big data concepts and technologies;
- 2
Write and interpret parallel database processing algorithms and methods;
- 3
Use big data processing frameworks and technologies;
- 4
Describe and compare NoSQL technologies;
- 5
Use and evaluate streaming methods in big data processing;
- 6
Use big data streaming technologies.
Workload and teaching
- Teaching approachActive learning
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 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.
Contacts
- Chief Examiners
- Associate Professor David Taniar
Common questions
What are the prerequisites for FIT5148?
You need FIT9132 and (FIT9131, FIT9133 or FIT9136) before you enrol. Enrolment rules also apply.
When is FIT5148 offered?
In 2020, FIT5148 runs in Semester 1 at Malaysia and Monash Online.
How much work is FIT5148?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT5148 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 2 other tasks.
More details
- Credit points
- 6
- Level
- 5
- Study level
- Postgraduate
- Faculty
- Faculty of Information Technology
- Type
- Coursework
- EFTSL
- 0.125
- Student contribution
- SCA Band 2
- Study abroad
- Not available
- Handbook years
- 2020