ACCT20081 - Financial Data Analytics

General Information

Unit Synopsis

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

Level Postgraduate
Unit Level 9
Credit Points 6
Student Contribution Band SCA Band 4
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).

Class Timetable View Unit Timetable
Residential School Optional Residential School
View Unit Residential School

Unit Availabilities from Term 2 - 2021

Term 2 - 2021 Profile
Brisbane
Melbourne
Online
Sydney
Term 1 - 2022 Profile
Brisbane
Melbourne
Online
Sydney
Term 2 - 2022 Profile
Brisbane
Melbourne
Online
Sydney
Term 3 - 2022 Profile
Brisbane
Online

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).

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.

Assessment Tasks

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

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

Past Exams

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Previous Feedback

Term 1 - 2020 : The overall satisfaction for students in the last offering of this course was 4.3 (on a 5 point Likert scale), based on a 44% response rate.

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.

Source: 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.The unit will undergo continual revision to keep up with latest trends and developments in data analytics.
Action Taken
No action necessary. In T220 the UC is teaching all cohorts.
Source: 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.
Action Taken
Nil.
Source: 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.
Action Taken
Nil.
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 Assessment Tasks to Learning Outcomes
Assessment Tasks Learning Outcomes
1 2 3 4 5
1 - Practical Assessment
2 - Project (applied)
3 - Take Home Exam
Alignment of Graduate Attributes to Learning Outcomes
Advanced Level
Professional Level
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
Alignment of Assessment Tasks to Graduate Attributes
Advanced Level
Professional Level
Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7
1 - Practical Assessment
2 - Project (applied)
3 - Take Home Exam