ACO5160 Introduction to accounting analytics
Faculty of Business and Economics
ACO5160 Introduction to accounting analytics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics. It isn't offered in 2022. It has no prerequisites.
- Credit points
- 6
- Offered in 2022
- Other periods
- Monash Online
- Assessment
- No exam
- 1 task
- Workload
- 144 hours
- per semester
This is the 2022 handbook entry. See the 2027 entry.
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Requisites
Before ACO5160
No prerequisites or corequisites besides the enrolment rules below.
After ACO5160
No unit lists ACO5160 as a prerequisite in the 2022 handbook.
Enrolment rules
You must be enrolled in course A6032, B4008, B6025 or B6028 to undertake this unit.
Overview
This unit brings together accounting and data analytics that are integral to facilitating decision making. Learning involves data mining, visualisation, optimisation, and regression analysis using accounting data. The IMPACT cycle of data analytics (identify the questions; master the data; perform test plan; address and refine results; communicate insights; track outcomes) is described and the process practiced in financial reporting, auditing, and managerial accounting contexts. You will identify questions, download data from, typically, Enterprise databases using SQL and other methods, perform testing using common business applications such as Excel, and communicate the results in a hands-on environment. You will compare and contrast different analytical tools to determine which one is best suited for each particular problem.
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| Teaching period 2 | Monash Online | Online |
| Teaching period 4 | Monash Online | Online |
Assessment
- Within semester assessmentThreshold hurdle100%
Learning outcomes
When you finish this unit, you should be able to:
- 1
understand the basic characteristics of financial accounting, auditing, and managerial accounting
- 2
analyse and interpret accounting information
- 3
understand and apply the core principles of and approaches to data analytics in the context of accounting
- 4
develop skills associated with data mining and machine learning
- 5
apply analytical skills in textual analytics
- 6
apply the use of advanced artificial intelligence to large accounting datasets.
Workload and teaching
- Tutorials18 hours
- Lectures18 hours
The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment, and preparation for scheduled activities. The unit requires on average six hours of scheduled activities per week. Scheduled activities may include a combination of teacher-directed learning, peer directed learning, and online engagement.
Contacts
- Chief Examiners
- Dr Jacob Raleigh
Common questions
What are the prerequisites for ACO5160?
ACO5160 has no prerequisites, but enrolment rules apply.
When is ACO5160 offered?
ACO5160 has no offerings listed in the 2022 handbook.
How much work is ACO5160?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ACO5160 have an exam?
No. ACO5160 has 1 assessment task and no exam.