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MA5831 - Advanced Data Management and Analysis using SAS

Credit points: 3
Year: 2020
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.

Subject Assessment

  • quizzes or tests (20%)
  • assignments (60%)
  • computational laboratories/log book (20%).
Prerequisites: 24CP OF POSTGRADUATE SUBJECTS

Availabilities

Cairns, Internal, Study Period 85
Census Date 10-Sep-2020
Workload expectations:

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

  • 26 hours tutorials
  • assessment and self-directed study

JCU Online, External, Study Period 81
Census Date 23-Jan-2020
Coordinator: Dr Carla Ewels
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

JCU Online, External, Study Period 85
Census Date 10-Sep-2020
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

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.