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Unit of study_

INFS6023: Data Visualisation

Semester 1, 2020 [Normal evening] - Camperdown/Darlington, Sydney

Data visualisation, story-telling, and scenario development have been identified as the most prominent analytical practices of tomorrow. This unit seeks to equip students with necessary knowledge and data visualisation skills, acquired through a real-life project inspired by the leading industry practices. Students will also develop a 'holistic' view of data visualisation in practice and will acquire 'thinking tools' to deal with its organisational and societal challenges. This unit focuses on business/organisational decision makers and their use of data visualisation. As such this unit does not require any prior IT, computer science or data science experience.

Unit details and rules

Unit code INFS6023
Academic unit Business Information Systems
Credit points 6
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Manoj Thomas,
Type Description Weight Due Length
Presentation group assignment Group project presentation
Oral presentation
15% Multiple weeks 15-25 minutes
Outcomes assessed: LO1 LO4 LO3 LO2
Small continuous assessment Quizzes
Small continuous assessment
20% Ongoing Ongoing
Outcomes assessed: LO1 LO4 LO3 LO2
Assignment Individual project
Written task
30% Week 07
Due date: 26 Apr 2020 at 23:59

Closing date: 06 May 2020
2500 words
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment group assignment Group project report
Written report
35% Week 11
Due date: 24 May 2020 at 23:59

Closing date: 03 Jun 2020
5000 words
Outcomes assessed: LO1 LO2 LO3 LO4
group assignment = group assignment ?

Assessment summary

  • Individual project: Use data visualisation techniques to address a business problem within a particular business case context.
  • Quizzes: Assess the knowledge and proficiency of topics discussed in class.
  • Group project report: The purpose of this assignment is to enable students to develop their thought and understanding of the topic areas, conduct research, stimulate broader thinking through collaborative teamwork and present their findings in written format.
  • Group project presentation: The purpose of this assignment is to enable students to express ideas in a manner relevant to decision makers. The assignment will enable students to develop essential business communication skills and assess their ability to correspond in oral and interactive forms.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.


50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 


0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to data visualisation Lecture (3 hr)  
Week 02 Data visualisation conceptual foundations Lecture (3 hr)  
Week 03 Introduction to Tableau Lecture (3 hr)  
Week 04 Quality of visual design Lecture (3 hr)  
Week 05 Data quality Lecture (3 hr)  
Week 06 Self study (mid semester exam week) Individual study (3 hr)  
Week 07 Infographics Lecture (3 hr)  
Week 08 Ethics of data visualisation Lecture (3 hr)  
Week 09 Visualisation principles and data governance Lecture (3 hr)  
Week 10 Visual story telling Lecture (3 hr)  
Week 11 Guided project work Lecture (3 hr)  
Week 12 Group presentations Lecture (3 hr)  
Week 13 Group presentations and unit summary Lecture (3 hr)  

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. apply the fundamental concepts and practice of data visualisation to analyse and present data-related challenges in any organisational setting (large or small)
  • LO2. identify and analyse multi-disciplinary issues, challenges and solutions with the use of data visualisation techniques
  • LO3. design and implement a small-scale data visualisation project in a real-life organisational setting, recommend and evaluate creative solutions and present the outcomes orally and in writing
  • LO4. demonstrate an awareness of the current and emerging data visualisation trends in business, High Ed and society, including data visualisation related ethical issues.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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