Big Data Analytics unit (KIT718)

Melbourne Study Centre, Ultimo Study Centre, Hobart

Introduction

In today's world, the prevalent use of technology and automation have resulted in an explosion in the quantity of data, often referred to as "big data", accumulated by business and by researchers. Data is seen as a critical asset for decision-making. Raw data, however, is of little value. In order to obtain insights from this big data analytical techniques are required to turn the data in the repositories into knowledge, by extracting information and identifying patterns, upon which actions can be taken. This unit will help students appreciate the value of using data mining techniques and information visualisation methods for the analysis of big data. Students will gain an understanding of various methods and techniques and applications for data mining. Students will also investigate information visualisation tools and techniques to represent the big data in forms that more readily convey embedded information. Students will gain an understanding of the major research issues in the area of big data.

Summary

Unit name	Big Data Analytics
Unit code	KIT718
Credit points	12.5
College/School	Sciences and Engineering School of Information and Communication Technology
Discipline	Information & Communication Technology
Coordinator	Doctor Wenli Yang
Delivered By	University of Tasmania and Third Party(ies): ECA
Level	Postgraduate

Availability

Location	Study period	Attendance options		Available to
Melbourne Study Centre	Semester 2
Ultimo Study Centre	Semester 2
Hobart	Semester 2

Note

Please check that your computer meets the minimum System Requirements if you are attending via Distance/Off-Campus.

Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.

Key Dates

Study Period	Start date	Census date	WW date	End date
Semester 2	5/7/2026	27/7/2026	30/8/2026	24/10/2026

* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).

Unit census dates currently displaying for 2026 are indicative and subject to change. Finalised census dates for 2026 will be available from the 1st October 2025. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

Learning Outcomes

• Explain and apply tools, techniques and research skills for analysing data
• Create and evaluate ICT components to support decision making based on user requirements
• Communicate and collaborate with stakeholders during the data analysis and decision-making process.

Fee Information

Field of Education	Commencing Student Contribution 1,3	Grandfathered Student Contribution 1,3	Approved Pathway Course Student Contribution 2,3	Domestic Full Fee 4
020119	$1,192.00	$1,192.00	not applicable	$2,919.00

• Available as a Commonwealth Supported Place
• HECS-HELP is available on this unit, depending on your eligibility³
• FEE-HELP is available on this unit, depending on your eligibility⁴

¹ Please refer to more information on student contribution amounts.
² Please refer to more information on eligibility and Approved Pathway courses.
³ Please refer to more information on eligibility for HECS-HELP.
⁴ Please refer to more information on eligibility for FEE-HELP.

If you have any questions in relation to the fees, please contact UniConnect or more information is available on StudyAssist.

Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.

Requisites

Prerequisites

KIT500 or KIT502 or KIT506 or KIT509

Teaching

Teaching Pattern	On-Campus enrolments in Hobart will follow the teaching arrangement: Lecture: 2 hours/week Tutorials: 2 hours/ week  Self-Study [Online Module]: up to 4 hours/week On-Campus Melbourne and Sydney teaching arrangements may differ and will be advised by your teaching team. For this unit, students are expected to attend lectures and on-campus classes and are expected to remain up-to-date with content that is delivered asynchronously online.
Assessment	Test 1 (20%)|Test 2 (25%)|Tutorial Task (25%)|Assignment 1 (30%)
Timetable	View the lecture timetable | View the full unit timetable

Textbooks

Required	Required readings will be listed in the unit outline prior to the start of classes.

The University reserves the right to amend or remove courses and unit availabilities, as appropriate.