Data Analytics for ICT Business
Credit points
(Generally, 1 credit = 10 hours of classes and independent study.)
Location
Online Real Time
VU Brisbane
VU Sydney
Prerequisites
(Or equivalent to be determined by unit coordinator)
Co-requisites
(Corequisite units must be studied concurrently with this unit)
Overview
In this unit, you will learn to explore data analytics in ICT business contexts, covering business intelligence, customer analytics, and AI-driven insights for strategic decision-making. You will apply advanced analytical techniques and visualisation tools to real-world problems, working in teams on hands-on projects. The unit also examines ethical, legal, and regulatory issues in data use. By the end, you will be equipped to evaluate analytics tools, generate actionable insights, and deliver data-driven recommendations: preparing you for roles in business analytics, data strategy, or further studies in enterprise intelligence.
Learning Outcomes
On successful completion of this unit, students will be able to:
- Determine data analytics methodologies, including AI-driven techniques, to solve complex business challenges in ICT enterprises;
- Evaluate data mining models, business intelligence tools, and visualisation techniques to support strategic decision-making;
- Compose data-driven business reports that incorporate actionable insights and recommendations for ICT business problems individually and as part of a team;
- Assess the ethical, legal, and regulatory considerations in business analytics, ensuring responsible data use in decision-making;
- Report and justify analytical insights using data visualisation and narrative techniques for business stakeholders.
Assessment
For Melbourne campuses
Assessment type: Test | Grade: 20%
Online test
Assessment type: Project | Grade: 35%
Business analytics project (Group) with demonstration, presentation and oral Q&A.
Assessment type: Case Study | Grade: 45%
Scenario-based data analytics and visualisation with Q&A verification.
Test: Students complete an online test assessing their understanding of data analytics methodologies and business intelligence tools applied to ICT business contexts.
Project: Includes structured milestone reviews and in-class progress checks. Student's individual contributions are logged, validated, and justified through recorded peer review or demonstration to ensure authenticity.
Case Study: Students apply concepts to unpredictable data science scenarios. Responses are evaluated based on reasoning, method selection, and outcome justification, with an in-class component or oral defence verifying understanding.
Other locations
Assessment type: Test | Grade: 20%
Online test
Assessment type: Project | Grade: 30%
Business analytics project (Group) with demonstration, presentation and oral Q&A.
Assessment type: Examination | Grade: 50%
Invigilated final written examination (3 hours)
Test: Students complete an online test assessing their understanding of data analytics methodologies and business intelligence tools applied to ICT business contexts. Project: Includes structured milestone reviews and in-class progress checks. Individual contributions are logged, validated, and justified through recorded peer review or demonstration to ensure authenticity. Examination: Invigilated, time-bound exam includes unseen data sets or problem types. Students must demonstrate deep understanding by explaining reasoning, performing analysis, and applying concepts to new contexts.
Required reading
Selected readings are provided on VU Collaborate.
As part of a course
This unit is studied as part of the following course(s):