Unit Outline

In today’s data economy, businesses are blessed and cursed with an abundance of data. This proliferation of data is creating new professions and changing existing professions. One profession that is witnessing a rapid change due to the explosion of data is accounting. While there exists a plethora of data available to businesses, accounting data remains a source of data that is reliable, relevant and accessible for all organizations. This unit will introduce students to the very recent changes ushered in by the big data revolution to the accounting profession, introduce students to how data analytics is being applied to accounting data, develop their skills in analyzing and presenting accounting data to management and also develop their abilities to critically evaluate the underlying accounting systems and processes related to both the collection, creation, processing and production of accounting data within organizations.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1.	Differentiate data analytics techniques used to address contemporary business challenges
2.	Compose compelling data-driven stories to provide business advice to a client
3.	Hypothesize solutions using business data analysis for contemporary business challenges

Requisites


REQUISITE TYPE	REQUISITES
Pre-requisite	N/A

Alterations as a result of student feedback

To be determined.

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	ASX100 company case study	Week 6	30 %	LO1, LO2, LO3
Assessment Task 2:	Online exam	Week 10	35 %	LO1, LO3
Assessment Task 3:	Data analytics case study	Week 13	35 %	LO1, LO2, LO3

Assessment details

Assessment Task 1: ASX100 company case study

Task Description:

Students will work in groups and select a ASX100 company where they will use accounting data to perform data analysis to assist the company in addressing a contemporary business challenge. The assignment comprises of a synchronous oral presentation in the workshops (15% - assessed individually) and a written report (15% - assessed as a group).

Task Length:

2000 words

Due Date:

Week 6

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Apply data visualisation techniques using software tools	LO2
2	Critically evaluate the quality of data inputs for data analytics	LO3
3	Evaluate the use of accounting data in data analytics application(s)	LO1
4	Create appealing and rich visualisations based on accounting data	LO2
5	Communicate the data story to management to support decision-making	LO2
6	Perform relevant analysis of data to support management decision-making	LO1
7	Critically evaluate the outputs produced from data analytics	LO3

Assessment Task 2: Online exam

Task Description:

Students will complete an online test consisting of multiple-choice, short answer and practical-based questions based on the topics covered from Week’s 1 to 8. This is a closed-book test and will be invigilated using Respondus Lockdown browser.

Task Length:

3 hours

Due Date:

Week 10

Weight:

35 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Critically evaluate the quality of data inputs for data analytics	LO3
2	Justify the right question(s) to solve a business problem	LO1
3	Evaluate accounting data using data analytics application(s)	LO1
4	Evaluate the relevance of a method of data analytics to a particular business question	LO3

Assessment Task 3: Data analytics case study

Task Description:

An individual assignment where students will apply various data analytic techniques relevant to accounting, learnt in the unit, to answer questions related to a large dataset of a fictitious company.

Task Length:

1500 words

Due Date:

Week 13

Weight:

35 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Explain the process of data analytics in an accounting context	LO1
2	Propose the right question(s) to solve a business problem	LO1
3	Explain the most common types of data visualisation tools used by accountants in data analytics	LO2
4	Distinguish between the four types of data analytics	LO3
5	Propose solutions to contemporary business challenges	LO3

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.

Review of results and appeals

You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.