Course Title: Accounting Data Analytics and Visualisation
Part A: Course Overview
Course Title: Accounting Data Analytics and Visualisation
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
ACCT2343 |
City Campus |
Undergraduate |
665H Accounting, Information Systems and Supply Chain |
Face-to-Face |
Sem 1 2023, Sem 2 2023, Sem 1 2024, Sem 2 2024 |
ACCT2344 |
RMIT University Vietnam |
Undergraduate |
665H Accounting, Information Systems and Supply Chain |
Face-to-Face |
Viet3 2023, Viet3 2024 |
ACCT2345 |
RMIT Vietnam Hanoi Campus |
Undergraduate |
665H Accounting, Information Systems and Supply Chain |
Face-to-Face |
Viet3 2024 |
ACCT2346 |
Singapore Inst of Management |
Undergraduate |
665H Accounting, Information Systems and Supply Chain |
Face-to-Face |
Offsh1 24, Offsh3 24, Offsh1 25 |
Course Coordinator: Assoc Prof Tarek Rana
Course Coordinator Phone: +61 3 9925 2583
Course Coordinator Email: tarek.rana@rmit.edu.au
Course Coordinator Location: Melbourne City Campus
Course Coordinator Availability: Appointment via email
Pre-requisite Courses and Assumed Knowledge and Capabilities
Required Prior Study
The following courses must be successfully completed before enrolling in this course:
- 054377 Business Decision Making
- 054376 Understanding the Business Environment
Course Description
Accounting professionals increasingly rely on data analytics and visualisation techniques for reporting to internal and external stakeholders. Data analytics and visualisation techniques are crucial to developing an analytic mindset. They provide rich insights for decision makers and help accountants communicate meaningful results to a variety of stakeholders.
Preparing and analysing accounting data and sharing results through effective communication techniques are increasingly important in accounting and other business professions who rely on accounting data for performance evaluation, resource allocation and investment decisions. The design of effective data analytics and visualisations and extract insights from big data can help communicate business insights for improved data-driven business decision making. Understanding and evaluating different types of data analytics and visualisation tools and techniques are critical in determining the appropriate types of techniques for creating meaningful accounting reports.
While accounting always has been about data analytics, in this course we show how the process of collecting, analysing, and using data has changed due to digital technologies. This course will develop critical thinking skills that are required to interact with big data, to discover new sources of accounting-related data, to comprehend the process needed to extract, clean and prepare the datasets before data analytics by considering data dimensions – veracity, velocity, variety, volume and value. This course will teach essentials for ensuring data quality so graduates have competencies in managing data quality, completeness, reliability, and/or validity.
This course provides you with the skills and ability to use digital technologies based on frameworks learnt in the curriculum, along with authentic assessments to solve business problems for long-term social impact. In this course, you will spend time reviewing reports, internal documents, spreadsheets, and presentations to synthesize market trends, competitive drivers, customer behaviours, and operational procedures for enhanced accounting reports. Working in teams are essential in this course and are effective ways to stay abreast of new developments in data analytics and visualisation.
Objectives/Learning Outcomes/Capability Development
.
You will achieve the following course learning outcomes (CLOs) upon successful completion of this course:
CLO1: Apply concepts, best practices and ethical guidelines to data analytics and visualisation in accounting reports.
CLO2: Develop digital competencies in preparing and analysing data for the generation of data visualisations across different accounting domains.
CLO3: Critically evaluate ethical concerns in data analytics and visualisation.
CLO4: Work individually or in teams to develop and communicate impactful visualisation techniques.
CLO5: Recommend effective visualisation techniques for sustainability-related narratives and long-term social impact.
Overview of Learning Activities
This course uses highly structured learning activities to guide your learning process and prepare you for the assessments. The activities are a combination of individual, peer-supported and facilitator-guided activities, and where possible project-led, with opportunities for feedback throughout.
The learning activities have been designed to assist you in the development of a number of important graduate capabilities. Authentic and industry-relevant learning is critical to this course, and you will be encouraged to critically compare and contrast what is happening in your preferred profession and/or industry, and to use your personal insights.
You are expected to consistently apply yourself to the course throughout the semester. Social learning is another important component, and you are expected to participate in class and group activities, share drafts of work and resources and give and receive peer feedback. You will be expected to work efficiently and effectively with others to achieve outcomes greater than those that you might have achieved alone.
Seminars/workshops are designed to supplement the material provided on the RMIT CANVAS site and the recommended readings. Discussions in seminars are specifically designed using group work and problem-solving activities so that you may gain clarification of topics covered throughout the semester. The seminar setting also provides the opportunity for you to critically evaluate problems and develop confidence in your ability to apply theoretical issues to practical situations.
Overview of Learning Resources
A range of texts and articles will be referred to in class. You will be given a list of suggested readings, but you are required to undertake further reading throughout the duration of the course. Feedback will be provided throughout the semester in class and/or in online discussion forums through individual and group feedback on practical exercises and individual consultation.
RMIT Library provides extensive resources, services and study spaces. All RMIT students have access to scholarly resources including course related material, books, e-books, journals and databases.
Computers and printers are available at every Library. You can access the Internet and Library e-resources. You can also access the RMIT University wireless network in the Library.
Contact: Ask the Library for assistance and information on Library resources and services: https://www.rmit.edu.au/library. Study support is available for assistance with assignment preparation, academic writing, information literacy, referencing, maths and study skills. Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period
Overview of Assessment
The assessment alignment list below shows the assessment tasks against the learning outcomes (CLOs).
Assessment Task 1: 20%
Linked CLOs 1, 2, 3
Assessment Task 2: 30%
Linked to CLOs 1, 2, 3, 4
Assessment Task 3: 50%
Linked to CLOs 1, 2, 3, 5