ITC575 Foundations of Big Data Analytics (8)

This subject introduces students to big data analytics as a tool for addressing and applying new analytical methods and algorithms to process large volumes of data in the context of information technology. Students will be introduced to the key practical concepts behind big data analytics. Students will also learn how to successfully extract value from massive volumes of structured and unstructured data to contribute towards informed decision making processes. Students will be provided an overview of the methods and techniques that help automate data analysis such as data mining, machine learning and artificial intelligence. Students will also be introduced to well-known software analytic tools used in this area.

Availability

Session 1 (30)
Online
Wagga Wagga Campus
Session 2 (60)
Online
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: ITC575. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Computing and Mathematics

Enrolment Restrictions

Only available to postgraduate students

Assumed Knowledge

Basic understanding of database structures is required to complete this subject successfully. Students without database knowledge are encouraged to enrol in ITC556 prior to attemtpting this subject.

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to discuss the basic concepts behind big data analytics and recognise the various types and sources of big data;
  • be able to explain the major stages of big data analytics life cycle;
  • be able to analyse the challenges associated in harvesting value from big data to empower decision making processes;
  • be able to interpret machine learning and artificial intelligence concepts in the context of big data analytics; and
  • be able to extract value from large data sets for informed decision making by utilizing some well-known software tools.

Syllabus

This subject will cover the following topics:
  • Introduction to big data
  • Need for big data analytics
  • Requirements of big data analytics
  • Role of big data analytics in Internet of Things (IoT)
  • Introduction to data analytic tools
  • Big data life cycle
  • Understanding the types of data
  • Methods of big data analysis
  • Applications of big data analytics

The information contained in the CSU Handbook was accurate at the date of publication: July 2020. The University reserves the right to vary the information at any time without notice.

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