MA5831 - Big Data: Management and Processing
|Student Contribution Band:
||College of Science and Engineering
This subject will provide students with cutting-edge tools and techniques for high-performance
and large-scale computing, with focus on computer models and software designed to
handle Big Data sets in a distributed and/or parallel fashion. Particular focus will
be given to distributed and parallel computing using Map-Reduce/Hadoop and similar
models for processing Big Data sets.
- list the different systems and approaches for high-performance and large-scale computing,
as well as explain their differences;
- conceptually describe and apply models for distributed and parallel computing of Big
Data sets, such as MapReduce and Spark;
- choose and apply different techniques and software for distributed and cloud computing
of Big Data, such as Hadoop.
||24CP OF POSTGRADUATE SUBJECTS
Study Period 83
|Census Date 16-May-2019
||Professor Ronald White
||Dr Neil Fraser, Mr Mostafa Shaikh.
The student workload for this
credit point subject is approximately
- 65 hours - Online resources including readings, screencasts, embedded quizzing
- assessment and self-directed study
|Method of Delivery:
||Online - JCU
||quizzes or tests (20%); assignments (60%); computational laboratories/log book (20%).
Minor variations might occur due to the continuous Subject quality improvement process,
and in case
of minor variation(s) in assessment details, the Subject Outline represents the latest