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MA5831 - Big Data: Management and Processing

Credit points: 3
Year: 2019
Student Contribution Band: Band 2
Administered by: 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.

Learning Outcomes

  • 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.
Prerequisites: 24CP OF POSTGRADUATE SUBJECTS

Availabilities

JCU Online, External, Study Period 83
Census Date 16-May-2019
Coordinator: Professor Ronald White
Lecturers: Dr Neil Fraser, Mr Mostafa Shaikh.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 65 hours - Online resources including readings, screencasts, embedded quizzing
  • assessment and self-directed study
Method of Delivery: Online - JCU
Assessment: quizzes or tests (20%); assignments (60%); computational laboratories/log book (20%).

Note: 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 official information.