Business Analytics and Visualisation
Credit points
(Generally, 1 credit = 10 hours of classes and independent study.)
Location
Online Real Time
VU Brisbane
VU Online
VU Sydney
Prerequisites
Co-requisites
(Corequisite units must be studied concurrently with this unit)
Overview
Business analytics and visualisation focuses on uncovering business insights hidden in massive datasets using statistical models and algorithms. Visualisation is the vital component of analysing data and communicating insights to stakeholders. The unit equips students with foundational knowledge in business analytics and visualisation to be able to analyse business data, convert insights into business decisions and communicate results to stakeholders. Using open source software (R and Python), students are exposed to a range of business analytics approaches and algorithms, including tidy data presentation, various data wrangling approaches, data storytelling and visualisation basics. Using project workflow and working with real world data, students learn how to work with different datatypes, build and evaluate models, develop data visualisation and communicate insights to stakeholders.
Learning Outcomes
On successful completion of this unit, students will be able to:
- Critically analyse the role of business analytics in supporting decision making in a modern organisation, with a focus of working with different data formats and data wrangling techniques;
- Investigate and assess different analytics solutions in open source environments (R/Python) to develop effective visualisations;
- Evaluate analytics models to uncover hidden patterns in business data and understand relationships between variables;
- Deconstruct and exemplify data communication strategies through reproducible reporting and collaborative practices with version control Git/Github; and,
- Exemplify creative and innovative problem-solving of complex professional challenges through the application of data analytics in the business domain.
- Participate in an academic community through reflective and critical engagement in academic texts and understanding of principles of academic integrity.
Assessment
For Melbourne campuses
Assessment type: Test | Grade: 25%
Practical exercises (5%, 10%, 10%)
Assessment type: Assignment | Grade: 35%
Data Analytics Project: a Kaggle style data analysis (data wrangling, modelling and visualisation)
Assessment type: Report | Grade: 40%
Research report (30%) and Presentation (10%) (Working with a real-world data to develop and evaluate a data model) - Group
Assessment type: Other | Grade: 0%
Evidence of completion of the Academic Integrity Modules (Hurdle)
Other locations
Assessment type: Assignment | Grade: 10%
Role of business analytics to support decision making processes
Assessment type: Assignment | Grade: 40%
Data Analytics Project using Kaggle for analysis and presentation (data wrangling)
Assessment type: Report | Grade: 50%
Research report (Working with a real-world data to develop and evaluate a data model)
Required reading
Selected readings will be made available via the unit VU Collaborate site.
As part of a course
This unit is studied as part of the following course(s):