Data Analytics for Business
Duration
- One Semester or equivalent
Contact hours
- 24 hours face to face + blended
On-campus unit delivery combines face-to-face and digital learning. For Online unit delivery, learning is conducted exclusively online.
Aims and objectives
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.
Unit Learning Outcomes (ULO)
On successful completion of this module the learner will be able to:
1. Exhibit fundamental data analytics techniques to transform, analyse and report on insights about datasets, using spreadsheet and database tools
2. Critically evaluate strategic priorities to support the implementation of dashboards and increase the level of data-driven decision making in an organisation
3. Present diagnostic analysis, and create and interpret prescriptive models to influence future organisational requirements
4. Evaluate the ethical and social issues of applying data analytics techniques in specific organisational contexts
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
On Campus Workshop | 3 | 8 | 24 |
Live Online Class | 1.5 | 8 | 12 |
Online Activities (asynchronous lecture) | 1.5 | 8 | 12 |
Unspecified Activities Independent Learning | 8.5 | 12 | 102 |
TOTAL | 150 hours |
Swinburne Online
Type | Hours per week | Number of Weeks | Total |
Online Activities | 15 | 10 | 150 |
TOTAL | 150 hours |
Assessment
Types | Individual/Group Role | Weighting | Unit Learning Outcomes (ULOs) |
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.
Reading materials
A list of reading materials/and or textbooks will be made available in the Unit Outline.