Data Analytics for Business
24 hours face to face + blended
One Semester or equivalent
Online
Overview
This unit aims to instruct students on the fundamental principles of information visualisation. Students will develop the ability to create visualisations that empower users to understand real-world data sets.
Requisites
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Quarter 4
Location
Online
Start and end dates
29-September-2025
30-November-2025
30-November-2025
Last self-enrolment date
29-September-2025
Census date
17-October-2025
Last withdraw without fail date
31-October-2025
Results released date
13-January-2026
Quarter 1
Location
Online
Start and end dates
19-January-2026
22-March-2026
22-March-2026
Last self-enrolment date
19-January-2026
Census date
10-February-2026
Last withdraw without fail date
24-February-2026
Results released date
14-April-2026
Quarter 2
Location
Online
Start and end dates
13-April-2026
14-June-2026
14-June-2026
Last self-enrolment date
13-April-2026
Census date
05-May-2026
Last withdraw without fail date
19-May-2026
Results released date
07-July-2026
Quarter 3
Location
Online
Start and end dates
06-July-2026
06-September-2026
06-September-2026
Last self-enrolment date
06-July-2026
Census date
28-July-2026
Last withdraw without fail date
11-August-2026
Results released date
29-September-2026
Quarter 4
Location
Online
Start and end dates
28-September-2026
29-November-2026
29-November-2026
Last self-enrolment date
28-September-2026
Census date
20-October-2026
Last withdraw without fail date
10-November-2026
Results released date
12-January-2027
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Exhibit fundamental data analytics techniques to transform, analyse and report on insights about datasets, using spreadsheet and database tools
- Critically evaluate strategic priorities to support the implementation of dashboards and increase the level of data-driven decision making in an organisation
- Present diagnostic analysis, and create and interpret prescriptive models to influence future organisational requirements
- Evaluate the ethical and social issues of applying data analytics techniques in specific organisational contexts
Teaching methods
Swinburne Online
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Online Directed Online Learning and Independent Learning | 15.00 | 10 weeks | 150 |
| TOTAL | 150 |
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Online Contact (Phasing out) Online Class | 1.50 | 8 weeks | 12 |
| Online Directed Online Learning and Independent Learning | 1.50 | 8 weeks | 12 |
| Face to Face Contact (Phasing out) Workshop | 3.00 | 8 weeks | 24 |
| Unspecified Learning Activities (Phasing out) Independent Learning | 12.75 | 8 weeks | 102 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Assignment 1 | Individual/Group | 40 - 60% | 1,2,4 |
| Assignment 2 | Individual | 40 - 60% | 2,3,4 |
Content
- Data-driven decision making
- Fundamental statistics and exploratory data analysis
- Working with databases and multiple data sets
- Diagnostic analytics
- Visualising data and creating Tableau Dashboards
- Data communication and storytelling with Tableau
- Introduction to predictive analytics
- Working as a professional data analyst
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.