Available in 2024
Course code

INFT6201

Units

10 units

Level

6000 level

Course handbook

Description

The pervasion of information technology into every aspect of life and the recent explosion of social media have resulted in the creation of huge volumes (Big Data) of typically unstructured data: web logs, videos, speech, photographs, purchase patterns, e-mails, GPS data and Tweets. Organisations have understood that there is a strong need for professional data analysts who are able to manage big data, to apply appropriate data analytics techniques (e.g. statistical learning, classification, and dimension reduction methods), and to utilise the critical knowledge within these enormous amounts of data. This course brings together several key theories and technologies used in manipulating, storing, and analyzing big data.


Availability2024 Course Timetables

Callaghan

  • Trimester 3 - 2024

Singapore NAIHE

  • Trimester 3 - 2024

Online

  • Trimester 3 - 2024

Sydney Elizabeth Street

  • Trimester 3 - 2024

Learning outcomes

On successful completion of the course students will be able to:

1. Investigate and explore the problems and limitations of existing enterprise technology in handling large datasets and how Big Data technologies can be used to overcome them.

2. Analyse the business requirements and applications of Big Data technologies.

3. Apply contemporary Big Data technologies to store, manipulate and analyse large unstructured data sets.


Content

Students will learn;

  1. The Characteristics of Big Data
  2. Structured, Unstructured and High Dimensional Data
  3. Data Intensive Distributed Applications and Architectures
  4. Data Analytics Techniques for Big Data
  5. Implementation of Data Analytics Techniques in Software Environments
  6. Extraction, communication and retention of Critical Knowledge from Big Data for Decision Support
  7. Integration of Big Data into Enterprise Systems
  8. Design and Production of Reports from Large Unstructured Datasets

Assumed knowledge

Exposure to modern Database technology


Assessment items

Project: Projects

Presentation: Presentation

Report: Data Analysis Report


Contact hours

Trimester 3 - 2024 - Callaghan

Computer Lab-1
  • Face to Face On Campus 2 hour(s) per week(s) for 11 week(s) starting in week 2
Online Activity-1
  • Online 2 hour(s) per week(s) for 12 week(s) starting in week 1

Trimester 3 - 2024 - Singapore NAIHE

Computer Lab-1
  • Face to Face On Campus 2 hour(s) per week(s) for 11 week(s) starting in week 2
Lecture-1
  • Face to Face On Campus 2 hour(s) per week(s) for 12 week(s) starting in week 1

Trimester 3 - 2024 - Online

Computer Lab-1
  • Online 2 hour(s) per week(s) for 11 week(s) starting in week 2
Online Activity-1
  • Online 2 hour(s) per week(s) for 12 week(s) starting in week 1

Trimester 3 - 2024 - Sydney Elizabeth Street

Computer Lab-1
  • Face to Face On Campus 2 hour(s) per week(s) for 11 week(s) starting in week 2
Online Activity-1
  • Online 2 hour(s) per week(s) for 12 week(s) starting in week 1

Course outline

Course outline not yet available.