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Hobart, Launceston

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 warehouses have been used to set up repositories for this big data. 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 business intelligence tools, data mining techniques and information visualisation methods for the analysis of big data. In this unit students will explore the concepts and technology of business intelligence and experience designing and building business intelligence systems. Students will also gain an understanding of various methods and techniques and applications for data mining. Students will also investigate information visualization 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 2021

Unit name Data Analytics
Unit code KIT306
Credit points 12.5
Faculty/School College of Sciences and Engineering
School of Information and Communication Technology
Discipline Information & Communication Technology
Coordinator

Quan Bai

Teaching staff

Level Advanced
Available as student elective? Yes
Breadth Unit? No

Availability

Note

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About Census Dates

Fees

Requisites

Prerequisites

KIT205 or KIT206 or KIT214

Teaching

Teaching Pattern

2hr lectures, 2hr online modules for self study, 2hr laboratory classes

Assessment

60% exam, 40% in-semester (2 assignments worth 15%, 25%)

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Textbooks

Required

Recommended

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