Unit rationale, description and aim
In the modern world, where data drives nearly every decision, the ability to effectively analyse and process it using computational tools has become indispensable. Businesses and organizations increasingly require professionals who can leverage advanced software and programming techniques to extract meaningful insights, automate analysis, and generate data-driven solutions that inform strategic decision-making. This unit provides students with both foundational and advanced knowledge in data analysis, interpretation, and visualization using industry-standard computing tools.
The unit introduces key technologies, platforms, and methodologies for data processing, visualization, and analytical modeling. Students will engage with specialized software such as Python, R, and Excel-based analytical tools to perform statistical analysis, machine learning, and dynamic visualizations. They will explore how algorithms and automation enhance data-driven processes, ensuring efficiency in handling large datasets and real-time analytics.
Additionally, the unit addresses the complexities of big data interpretation, emphasising strategies for managing scalability, computational efficiency, and ethical considerations in algorithmic decision-making. By developing technical proficiency in computational tools, students will be equipped to transform raw data into actionable insights, effectively communicating findings to both technical and non-technical audiences.
Campus offering
No unit offerings are currently available for this unit.Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
Analyse the principles of data analysis and profes...
Learning Outcome 01
Apply critical thinking to evaluate the importance...
Learning Outcome 02
Utilise data analysis and visualisation tools to t...
Learning Outcome 03
Evaluate contemporary and innovative data visualis...
Learning Outcome 04
Analyse ethical dilemmas, including privacy and se...
Learning Outcome 05
Content
Topics will include:
· Introduction to data analysis and visualisation
· Principles of data analysis
· Fundamentals of data visualisation
· Different types of data visualisations and their effectiveness
· Challenges of interpreting and visualising big data
· Ethical considerations in data Analysis and visualisation
· Designing meaningful visualisations for target audiences
· Emerging trends and innovations in data analysis and visualisation.
Assessment strategy and rationale
To pass this unit, students are required achieve an aggregate mark of at least 50% and demonstrate achievement of all learning outcomes (LOs).
The first assessment is a concise brief designed to evaluate students’ understanding of fundamental data analysis and visualisation concepts, including common techniques and their significance. This foundational assessment ensures that students have a solid understanding of essential data analysis concepts. The second assessment is a practical report that allows students to apply their knowledge of data analysis and visualisation by demonstrating critical thinking, analysing the given dataset, and employing advanced analytical techniques and visualisation tools to derive actionable insights. This assessment builds upon the foundational knowledge established in the first assessment, allowing students to deepen their analytical skills and refine their ability to interpret complex datasets. The final assessment focuses on pitching the use of advanced data analysis and visualisation techniques to support strategic decision-making within an organisation. Students are required to explore innovative data visualisation approaches to effectively present organisational insights and critically evaluate ethical dilemmas, including privacy and security concerns. This final assessment integrates the knowledge and skills acquired in the previous assessments, demonstrating the students' ability to apply their learning to real-world, strategic contexts.
Overview of assessments
Assessment Task 1: Brief: Students will prepare ...
Assessment Task 1: Brief: Students will prepare a 1000-word brief on the critical role of data analysis and visualisation within a business context of their choice. The brief should summarise and discuss the significance, best practices, and impacts of data analysis and visualisation on business decision-making. They will have to select a task to address a real-world problem using the principles of data visualisation and submit the project proposal for it.
Submission type: Group
Artifact: Project proposal
20%
Assessment Task 2: Report : This assessment requi...
Assessment Task 2: Report: This assessment requires students to complete a practical project involving the analysis of a given dataset. Students must demonstrate critical thinking by analysing the dataset and applying advanced analytical techniques and visualisation tools to derive actionable insights. The purpose of this assessment is to evaluate the students' ability to translate their knowledge of data analysis and visualisation into practical applications.
Submission type: Group
Artifact: Program and report including contribution of the team members
40%
Assessment Task 3: Business presentation: A 6–8-...
Assessment Task 3: Business presentation: A 6–8-minute presentation pitching advanced data analysis and visualisation techniques to support strategic decision-making, with a focus on innovative approaches and ethical considerations. They will have to showcase the program to demonstrate how their solution has solved the problem of their choice.
Submission type: Group
Artifact: Program and presentation including contribution of the team members
40%
Learning and teaching strategy and rationale
Students should anticipate undertaking 150 hours of study for this unit over a twelve-week semester or equivalent study period, including class attendance, readings, online forum participation and assessment preparation.
This unit may be offered in “Attendance” and/or “Online” mode to cater for the learning needs and preferences of a range of participants.
Attendance Mode
Students will require face-to-face attendance in blocks of time determined by the school. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for students to prepare and revise.
Online Mode
This unit utilises an active learning approach whereby students will engage in e-module activities, readings and reflections, and opportunities to collaborate with peers in an online environment. This can involve, but is not limited to, online workshops, online discussion forums, chat rooms, guided reading, and webinars. Pre-recorded lectures will be incorporated within the online learning environment and e-modules. In addition, electronic readings will be provided to guide students’ reading and extend other aspects of online learning.