The course covers the fundamental understanding of accounting and auditing data analytics.

■ Develops an analytical mindset supported by the provided toolkit to extract, transform, validate and visualise the data.

■ apply data analytics by auditors to evaluate firm data and generate support for management assertion,

■ to apply data analytics for measuring performance while the company is working toward the targeted goals,

■ to access and analyse the financial statement data, to familiarise with the XBRL taxonomy.

8 2h workshops and 2 2h tutorials

None

None

An individual project report (75%) and a group work with a video presentation (25%)

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

The aims of this course are:

■ develop general decision-making and problem-solving skills using data analytics methods and tools in accounting and audit context. 

■ develop the ability to model and evaluate business questions

■ present and refine findings using visualisation

1. Hypothesise business questions and use data analytics to answer those questions.

2. Obtain, transform, and extract reliable data from accounting systems and other sources. Critically evaluate data sources.

3. Make Model and evaluate the data using supervised and unsupervised approaches. 

4. Report and justify their analysis with appropriate visualisations for different stakeholders.

5. Be able to estimate predictive analysis for financial accounting, management accounting and auditing tasks.

6. Work collaboratively in a group to produce a combined piece of coursework, by liaising with other class members, allocating tasks and co-ordinating group meetings.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.