CQUniversity Unit Profile
ACCT20081 Financial Data Analytics
Financial Data Analytics
All details in this unit profile for ACCT20081 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

As the economy moves towards more digital disruption, management and auditors are seeking innovative technologies for generating timely information for decision making. The unit is designed to provide you with an understanding of how financial data of an organisation can be analysed in a timely manner using data analytics. You are introduced to concepts, tools, software and methodologies of business intelligence and how they are applied to the analysis of financial data. You will gain experience in analysing accounting audit trails, using audit software, detecting potential fraud, visualising data, and generating dashboards for performance reporting. This unit is suitable for students with minimal information systems background.

Details

Career Level: Postgraduate
Unit Level: Level 9
Credit Points: 6
Student Contribution Band: 10
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Pre-requisite ACCT20071 Foundations in Accounting and ACCT20072 Accounting Systems & Information Assurance OR ACCT20070 Accounting in Australia and ACCT28001 Business Analytics Techniques

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Term 1 - 2021

Brisbane
Melbourne
Online
Sydney

Attendance Requirements

All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Residential Schools

This unit has a Optional Residential School for distance mode students and the details are:
Click here to see your Residential School Timetable.

Class and Assessment Overview

Recommended Student Time Commitment

Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Class Timetable

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Practical Assessment
Weighting: 20%
2. Project (applied)
Weighting: 30%
3. Take Home Exam
Weighting: 50%

Assessment Grading

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

Previous Student Feedback

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Informal student comments

Feedback

Students appreciated the applied nature of the unit, providing exposure to a range of real-world data analytics software, and their application in accounting, fraud detection and auditing.

Recommendation

These strengths of the unit were strongly appreciated by students and will be continued.

Feedback from Informal student comments

Feedback

Students requested more worked examples relating to SAS and Tableau.

Recommendation

More time will be allocated to demonstrating examples during the Workshop sessions.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Describe and distinguish data concepts, decision support systems, data warehouses, and data analytics, and perform querying of data
  2. Apply data analytics and data visualisation software to provide information for management and auditors
  3. Analyse data structures and extract accounting audit trails from computerised accounting systems
  4. Design audit procedures and apply audit software in substantive testing and fraud detection
  5. Apply performance management principles and develop performance dashboards and other visual presentations for management.


Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3 4 5
1 - Practical Assessment - 20%
2 - Project (applied) - 30%
3 - Take Home Exam - 50%

Alignment of Graduate Attributes to Learning Outcomes

Graduate Attributes Learning Outcomes
1 2 3 4 5
1 - Knowledge
2 - Communication
3 - Cognitive, technical and creative skills
4 - Research
5 - Self-management
6 - Ethical and Professional Responsibility
7 - Leadership

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7
1 - Practical Assessment - 20%
2 - Project (applied) - 30%
3 - Take Home Exam - 50%
Textbooks and Resources

Textbooks

There are no required textbooks.

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • Microsoft Excel
  • SAS On Demand
  • Tableau
Referencing Style

All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)

For further information, see the Assessment Tasks.

Teaching Contacts
Kishore Singh Unit Coordinator
k.h.singh@cqu.edu.au
Schedule
Week 1 Begin Date: 08 Mar 2021

Module/Topic

Introduction

Business case for data analytics

SAS Studio Demonstration

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

SAS Computer Workshop 1

Week 2 Begin Date: 15 Mar 2021

Module/Topic

Data concepts, data quality, data warehouses

Introduction to SAS Programming

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

SAS Computer Workshop 2

Week 3 Begin Date: 22 Mar 2021

Module/Topic

Big Data

SAS Programming 1

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

SAS Computer Workshop 3
Week 4 Begin Date: 29 Mar 2021

Module/Topic

Structured Query Language (SQL)

Data matching

SAS Programming 2

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

SAS Computer Workshop 4

Week 5 Begin Date: 05 Apr 2021

Module/Topic

Audit Trails

Data extraction and preparation

SAS Programming 3

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

SAS Computer Workshop 5

Vacation Week Begin Date: 12 Apr 2021

Module/Topic

No classes this week.

Chapter


Events and Submissions/Topic

Week 6 Begin Date: 19 Apr 2021

Module/Topic

Developing audit procedures

Applying audit software in substantive testing

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

MS Excel Computer Workshop 1

Week 7 Begin Date: 26 Apr 2021

Module/Topic

Fraud Detection

Benford’s Law

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

MS Excel Computer Workshop 2



Practical Assessment Due: Week 7 Friday (30 Apr 2021) 5:00 pm AEST
Week 8 Begin Date: 03 May 2021

Module/Topic

Future of Audit

Continuous auditing and controls monitoring

Introduction to Tableau

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

Tableau Computer Workshop 1

Week 9 Begin Date: 10 May 2021

Module/Topic

Data Visualization

Data analysis in Tableau

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

Tableau Computer Workshop 2

Week 10 Begin Date: 17 May 2021

Module/Topic

Dashboards and performance reporting

Charts and Dashboards in Tableau

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

Tableau Computer Workshop 3

Week 11 Begin Date: 24 May 2021

Module/Topic

Mapping Data

Maps in Tableau

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

Tableau Computer Workshop 4



Project Due: Week 11 Friday (28 May 2021) 5:00 pm AEST
Week 12 Begin Date: 31 May 2021

Module/Topic

Unit review

Chapter

Lecture notes and materials are available in Moodle

Events and Submissions/Topic

No Computer Workshop this week

Review/Exam Week Begin Date: 07 Jun 2021

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 14 Jun 2021

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Practical Assessment

Assessment Title
Practical Assessment

Task Description

Students perform a series of data analytics tasks to demonstrate their knowledge, understanding and skills in using the SAS software platform.


Assessment Due Date

Week 7 Friday (30 Apr 2021) 5:00 pm AEST


Return Date to Students

Week 9 Friday (14 May 2021)


Weighting
20%

Assessment Criteria

This assessment item evaluates the student's ability to use SAS software to perform basic tasks covered in weeks 1 to 5.


Referencing Style

Submission
Online

Submission Instructions
Submit SAS programs and associated output files, online via Moodle. Emailed submissions will not be accepted.

Learning Outcomes Assessed
  • Describe and distinguish data concepts, decision support systems, data warehouses, and data analytics, and perform querying of data
  • Apply data analytics and data visualisation software to provide information for management and auditors


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Research
  • Self-management

2 Project (applied)

Assessment Title
Project

Task Description

Students select and perform appropriate data analytics procedures using a combination of software tools and provided data. They apply principles learnt in the unit to analyse data and develop visual presentations to produce relevant reports. They report their findings in a professionally-documented report to management.


Assessment Due Date

Week 11 Friday (28 May 2021) 5:00 pm AEST


Return Date to Students

Review/Exam Week Friday (11 June 2021)


Weighting
30%

Assessment Criteria

This assessment will assess the student's ability to: identify analytics problems, select suitable procedures and software tools, solve problems and report findings that are supported by appropriate visualisations.


Referencing Style

Submission
Online

Submission Instructions
Submit Tableau files and final report, online via Moodle. Emailed submissions will not be accepted.

Learning Outcomes Assessed
  • Apply data analytics and data visualisation software to provide information for management and auditors
  • Analyse data structures and extract accounting audit trails from computerised accounting systems
  • Design audit procedures and apply audit software in substantive testing and fraud detection
  • Apply performance management principles and develop performance dashboards and other visual presentations for management.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Research
  • Self-management

3 Take Home Exam

Assessment Title
Take Home Exam

Task Description

This is a written assessment consisting of theory and programming questions covering content from weeks 1 to 12.


Assessment Due Date

Scheduled during Final Exam Week. Refer to exam timetable which will be made available in Moodle


Return Date to Students

Weighting
50%

Assessment Criteria

All content covered in weeks 1 to 12 are examined.


Referencing Style

Submission
Online

Submission Instructions
Submit answer file online via Moodle. Hand-written or emailed submissions will not be accepted.

Learning Outcomes Assessed
  • Describe and distinguish data concepts, decision support systems, data warehouses, and data analytics, and perform querying of data
  • Analyse data structures and extract accounting audit trails from computerised accounting systems
  • Design audit procedures and apply audit software in substantive testing and fraud detection
  • Apply performance management principles and develop performance dashboards and other visual presentations for management.


Graduate Attributes
  • Knowledge
  • Cognitive, technical and creative skills

Academic Integrity Statement

As a CQUniversity student you are expected to act honestly in all aspects of your academic work.

Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.

When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.

Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.

As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.

What is a breach of academic integrity?

A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.

Why is academic integrity important?

A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.

Where can I get assistance?

For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.

What can you do to act with integrity?