22579 Data Visualisation for Business Communication
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 22576c Fundamentals of Business Data Analytics
The lower case 'c' after the subject code indicates that the subject is a corequisite. See definitions for details.
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Description
This subject focuses on the art and science of presenting complex business data in a visually compelling and informative manner. Students in this subject learn to use various tools and techniques to create meaningful charts, graphs, dashboards, and interactive visuals to convey key insights from data. Through hands-on projects and case studies, they gain a deep understanding of how effective data visualization can enhance decision-making, storytelling, and overall communication in the business world. This subject equips students with the skills needed to make data-driven decisions and communicate their findings clearly and persuasively to diverse audiences.
Subject learning objectives (SLOs)
| 1. | Analyse and interpret complex business data and identify key features that are relevant to decision-making and strategic communication |
|---|---|
| 2. | Apply principles of visual design to create visuals that are clear, aesthetically pleasing, and effectively convey information to a target audience |
| 3. | Design interactive dashboards and visualisations that allow users to explore data dynamically, facilitating deeper insights and enabling stakeholders to make informed business decisions |
| 4. | Construct a narrative around data to communicate a cohesive and persuasive business story |
| 5. | Evaluate the ethical aspects of data visualisation to promote responsible and transparent communication in the business context |
Contribution to the development of graduate attributes
Designed to address the growing need for business graduates to be ‘dataviz’, this subject equips students with the skills and knowledge necessary to leverage data visualization as a powerful tool for clear and effective business communication. It also challenges students to broaden their horizons, adopt new ways of thinking and embrace the promise of a smarter, better future achievable through data analytics and industry-standard data visualisation tools and software. The subject contributes to all four graduate attributes of the Bachelor of Business, with particular emphasis on critical thinking and analytical skills (GA1), being storytellers and effective communicators of complex information to a wide audience (GA2) as well as social responsibility and cultural awareness (GA3) through to technical and professional skills (GA4) to operate effectively in business. The subject also contributes to the development of Program Learning objectives in the Business Data Analytics major.
- Apply evidence, creativity, and critical reasoning to solve business problems (1.1)
- Communicate information clearly in a form appropriate for its audience (2.1)
- Make judgements and business decisions consistent with the principles of social responsibility and inclusion (3.1)
- Apply technical and professional skills to operate effectively in business (4.1)
Teaching and learning strategies
This subject uses a variety of teaching and learning strategies to provide students with a hands-on approach to learning about data and analytics utilizing multiple technologies to analyse business data and communicate the outcome. Classes are interactive and are used to impart important theoretical and practical concepts. Students work through and are assessed on several lab exercises that utilize data from real companies.
Feedback is provided regularly in several different formats: discussions of questions and problems with peers, feedback from the lecturer/tutor on ideas presented and results/feedback of assessment tasks and automated feedback through learning activities on the UTS LMS (Canvas). This feedback is provided timely throughout the session.
Pre-class work: Students are required to work through learning content presented on the UTS LMS (Canvas) or other platforms before attending class and acquaint themselves with skills and technologies used in the subject (e.g., Excel, Tableau).
In-class: In the class, students will complete questions individually or as a group on concepts and different business analytic problems. Students will enhance their understanding and learning experience by engaging in the solution of the problems in small groups and presenting their ideas to peers or the entire class. Students are encouraged to become active engaged learners and they need to understand both fundamental methods/concepts as well as the tools to be able to deliver solutions.
Content (topics)
- Introduction to data analytics and visualization
- Communication of results (storytelling) using data visualisation
- Chart types, graphs, maps and dashboards, and their benefits and pitfalls
- Analytics and data visualisation applications in practice (e.g., marketing, accounting, finance, and operations)
Assessment
Assessment task 1: Online Quizzes (Individual)*
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 5 |
|---|---|
| Weight: | 20% |
| Length: | 10-15 minutes |
| Criteria: |
*Note: Late submission of the assessment task will not be marked and awarded a mark of zero. |
Assessment task 2: Tutorial Problems (Group)*
| Objective(s): | This addresses subject learning objective(s): 1, 2, 3, 4 and 5 |
|---|---|
| Weight: | 20% |
| Length: | 60 to 90 minutes in class time |
| Criteria: |
*Note: Late submission of the assessment task will not be marked and awarded a mark of zero. |
Assessment task 3: Visualisation Project (Individual)*
| Intent: | Part 1: Project Plan (20%) |
|---|---|
| Objective(s): | This addresses subject learning objective(s): 1, 2, 3, 4 and 5 |
| Weight: | 60% |
| Length: | Part 1: report: 500-1,000 words |
| Criteria: | Part 1:
*Note: Late submission of the assessment task will not be marked and awarded a mark of zero. |
Minimum requirements
A student must achieve 50% or more of the subject’s total marks AND achieve 40% or more in the final assessment to pass the subject.
A Fail (X) Grade is awarded to a student who attain 50% or more of the overall subject assessment marks but attain less than 40% of the final assessment marks. To pass the subject, the student must then attain 50% or more of the marks in the supplementary task, in which case the student is awarded an overall mark of 50P.
Required texts
- Richardson, V. and Watson, M. (2024) Introduction to Business Analytics, McGraw Hill.
- Readings for 22579
References
- Camm, J.D. et al (2022) Data Visualization: Exploring and Explaining with Data, Cengage.
- Berinato, S. (2024) Good Charts, Updated and Expanded: The HBR Guide to Making Smarter, More Persuasive Data Visualisations, Harvard Business Review Press.
- Cole Nussbaumer Knafic, (2015), Storytelling with Data, Wiley
- Nancy Duarte, Persuasive Presentations, (2012), HBR Guide to, Harvard Business Review Press.
- Jonathan Schwabish, (2021), Better Data Visualisations: A Guide for Scholars, Researchers, and Wonks, Columbia University Press.
- Claus O Wilke (2019) Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, O'Reilly Media.
- Kristen Sosulski (2018) Data Visualization Made Simple,1st ed.. RoutlRoutledge, NY.
- Lindy Ryan (2018) Visual Data Storytelling with Tableau, 1st ed. O'Reilly.
- Meagan Longoria (2019) Power BI Data Visualization with Purpose: Communicating through Color, Shape and Layout, Apress (Video).
- Meagan Longoria (2019) Power BI Data visuals that impact and persuade, Springer (Video).
- Jeffrey Heer (2015) Effective Data Visualization, OReilly (Video)