Overview

This unit equips students with the knowledge and skills to transform data into actionable insights and foresights for enhanced organisational decision-making. Emphasising the strategic value of Business Intelligence (BI), students learn to harness data from diverse sources using visual analytics, data analytics, and enterprise-grade BI tools. The unit explores how data-driven approaches support both short- and long-term organisational goals, with practical application of analytics platforms to derive actionable intelligence. The unit also introduces the practical potential of Artificial Intelligence and Machine Learning in enhancing analytical outputs, enabling students to appreciate their emerging role in transforming raw data into strategic, enterprise-ready intelligence.

Requisites

Prerequisites
INF10025 Data Management and Analytics

AND

125 credit points from a single degree OR 150 credit points from a double degree
AND either,
INF20003 Requirements Analysis and Modelling
OR
INF20016 Big Data Management

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
02-March-2026
31-May-2026
Last self-enrolment date
15-March-2026
Census date
31-March-2026
Last withdraw without fail date
21-April-2026
Results released date
07-July-2026
Semester 2
Location
Hawthorn
Start and end dates
03-August-2026
01-November-2026
Last self-enrolment date
16-August-2026
Census date
01-September-2026
Last withdraw without fail date
22-September-2026
Results released date
08-December-2026

Unit learning outcomes

Students who successfully complete this unit will be able to:

  1. Demonstrate a critical understanding of the strategic value of data, analytics, and Business Intelligence in supporting data-driven organisational decision-making
  2. Contextualise business problems to determine appropriate data requirements to generate analytical insight and foresight
  3. Apply Business Intelligence or data analytics tools to analyse organisational datasets and provide data-driven insights to an organisation’s complex problems
  4. Evaluate the technological, organisational, ethical, and managerial considerations influencing the implementation and adoption of Business Intelligence or AI-enabled analytics solutions

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-campus
Class
2.00 12 weeks 24
Online
Lecture
1.00 12 weeks 12
Unspecified Activities
Independent Learning
9.50 12 weeks 114
TOTAL150

Assessment

Type Task Weighting ULO's
Portfolio Individual  20-40%  1,4
Project Individual  30-50%  1,2,3
Test Individual  20-30%  2,3

Content

  • Strategic value of Business Intelligence and its role in data-driven organisational decision-making
  • Data sources, types (structured and unstructured), metadata
  • Governance, data privacy, legal, and ethical considerations
  • Data management, modelling, warehousing, data lake, master data management
  • Descriptive, diagnostic, and predictive analytics, monte-carlo analysis, OLAP, OLTP
  • Knowledge discovery and data mining including classification, clustering, and association methods
  • Data visualisation and dashboard design principles for effective analytical storytelling
  • Introduction to Artificial Intelligence and Machine Learning in Business Intelligence

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.