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Unit outline_

INFS2050: Data Governance and Technology Assurance

Semester 1, 2022 [Normal day] - Remote

Data governance is a major imperative for organisations in effectively managing, using, protecting and leveraging their critical data assets. This unit introduces students to key concepts, processes, technologies and stakeholders related to the design and implementation of a data governance program. The unit takes an interdisciplinary and multi-level approach that examines standards, frameworks and methodologies for managing data quality, protecting critical and sensitive information, supporting business analytics and meeting compliance obligations. In examining different stages of the data lifecycle, students also learn about legal, professional and ethical responsibilities, policy implications, required skill sets and accountabilities.

Unit details and rules

Academic unit Business Information Systems
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
INFS3010 or INFS3030
Assumed knowledge
? 

INFS1000 or INFO1000 or INFO1003 or INFO1903

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Catherine Hardy, catherine.hardy@sydney.edu.au
Lecturer(s) Catherine Hardy, catherine.hardy@sydney.edu.au
Type Description Weight Due Length
Assignment Individual Assignment: A
Please see detailed Individual Assignment requirements in Canvas
25% Week 05
Due date: 25 Mar 2022 at 00:00

Closing date: 11 Apr 2022
Equivalent to 1500 words
Outcomes assessed: LO1 LO5 LO6 LO4
Assignment group assignment Group Assignment
Please see detailed Group Assignment requirements/components on Canvas.
30% Week 12
Due date: 18 May 2022 at 12:00

Closing date: 18 May 2022
Equivalent effort to 1800 words
Outcomes assessed: LO2 LO5 LO6 LO7
Assignment Individual Assignment: B
Please see detailed Individual Assignment requirements in Canvas.
45% Week 13
Due date: 27 May 2022 at 00:00

Closing date: 10 Jun 2022
Equivalent to 2700 words
Outcomes assessed: LO2 LO3 LO4 LO6 LO1
group assignment = group assignment ?

Assessment summary

Individual Assignment A: This assignment will require you to integrate information from weekly lectures and tutorials to create a concise written report.

Individual Assignment B: This assignment will require you to integrate information from lectures and tutorials to create a concise written report.

Group Assignment: This assignment consists of a presentation as well as other written and non-written elements. 

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

Description

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. 

Distinction

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.

Credit

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.

Pass

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. 

Fail

0 - 49

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

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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: The Data Governance Imperative Lecture (3 hr) LO1
Week 02 History and context of data governance Lecture and tutorial (3 hr) LO1 LO3 LO5 LO6 LO7
Week 03 Data governance: definitions, principles and frameworks Lecture and tutorial (3 hr) LO1 LO4 LO6 LO7
Week 04 Self Directed Learning Tutorial (3 hr) LO1 LO3 LO4 LO5 LO6 LO7
Week 05 Directed data, surveillance and governance Lecture (3 hr) LO3 LO4 LO6 LO7
Week 06 Volunteered data, analytics and governance Lecture and tutorial (3 hr) LO3 LO4 LO6 LO7
Week 07 Automated data, platforms and governance Lecture and tutorial (3 hr) LO3 LO4 LO6 LO7
Week 08 Data ethics and data governance Lecture and tutorial (3 hr) LO2 LO5 LO6 LO7
Week 09 Data integrity and data governance Lecture and tutorial (3 hr) LO2 LO5 LO6 LO7
Week 10 Data security and data governance (Part 1) Lecture and tutorial (3 hr) LO2 LO5 LO6 LO7
Week 11 Data security and data governance (Part 2) Lecture and tutorial (3 hr) LO2 LO5 LO6 LO7
Week 12 Group Presentation and Evaluation Presentation (3 hr) LO6 LO7
Week 13 Business Use Cases for Data Governance Project (3 hr) LO1 LO2 LO3 LO4 LO5 LO6

Attendance and class requirements

All lectures are recorded and will be available on Canvas together with weekly class requirements. 

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.

Required readings

Details about prescribed readings for this unit are available on Canvas.

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. describe key concepts and principles of data governance and explain their importance in business information systems
  • LO2. demonstrate knowledge of the relationship of data governance with security, privacy, ethics and regulatory functions
  • LO3. identify key stakeholders involved in governing data in different and changing institutional contexts and technology platforms
  • LO4. demonstrate knowledge of key data governance standards and frameworks and practise their application through class activities and assigned tasks
  • LO5. conduct research to develop and support arguments about key issues, challenges and trends associated with data governance in business
  • LO6. communicate in oral and written form your knowledge, thoughts and findings through class discussions, group work and individual assignments
  • LO7. provide constructive feedback to your peers on their written work, and address issues identified by your instructor and peers when reflecting and revising your own written work.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

Changes to the assessment design and sequencing of topics have been made in response to student feedback since the unit was last offered.

Disclaimer

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

To help you understand common terms that we use at the University, we offer an online glossary.