Availabilities:

Location Domestic International
Gold Coast Session 2 Session 2
Lismore Session 2 Session 2
Melbourne N/A Session 2
Online Session 2 N/A
Perth N/A Session 2
Sydney N/A Session 2

Unit Summary

Unit type

UG Coursework Unit

Credit points

12

AQF level

7

Level of learning

Advanced

Unit aim

Provides students with the necessary knowledge and skills to effectively use business analytics to support decision making in the context of ‘big data’ as a strategic resource. As a ‘data-driven’ unit, students will be exposed to a variety of analytical techniques using software applications.

Unit content

Topic 1: Introduction to business analytics

Topic 2: Data visualisation

Topic 3: Dimension reduction

Topic 4: Evaluation of predictive performance

Topic 5: Multiple linear regression

Topic 6: k-Nearest Neighbours (k-NN)

Topic 7: Logistic regression

Topic 8: Association rules and collaborative filtering

Topic 9: Cluster analysis

Topic 10: Forecasting - Part I

Topic 11: Forecasting - Part II

Topic 12: Revision

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

GA1: , GA2: , GA3: , GA4: , GA5: , GA6: , GA7:
On completion of this unit, students should be able to: GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource.
2 Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage.
3 Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes.
4 Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings.

On completion of this unit, students should be able to:

  1. Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource.
    • GA4:
    • GA6:
  2. Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage.
    • GA1:
    • GA4:
  3. Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes.
    • GA4:
  4. Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings.
    • GA1:
    • GA6:

Prescribed texts

  • An e-book of the following is also available (ISBN: 978-1-118-87933-7): Shmueli, G, Bruce, PC, Yahav, I, Patel, NR & Lichtendahl, KC Jr, 2017, Data Mining for Business Analytics: Concepts, Techniques, and Applications in R, Wiley. ISBN: 978-1-118-87936-8.
Prescribed texts may change in future teaching periods.