Data Analytics for Accounting and Finance ACCFIN4090
- Academic Session: 2024-25
- School: Adam Smith Business School
- Credits: 20
- Level: Level 4 (SCQF level 10)
- Typically Offered: Semester 1
- Available to Visiting Students: Yes
- Collaborative Online International Learning: No
Short Description
The course covers the fundamental understanding of accounting analytics and auditing data analytics. It defines and explains the impact of data analytics on the business and accounting profession. In addition, it develops an analytical mindset supported by the provided toolkit to extract, transform, validate, and visualise the data. The course includes various models and techniques used for data analytics as an increasingly important skill for accountants. All the techniques are supported with accounting-specific examples.
Timetable
Synchronous learning activities:
Workshop (2 hours x 10 weeks)
Tutorials (2 hours x 2 weeks)
Asynchronous learning activities will consist of concept explanation and case solution videos, totalling 12 hours across the semester
Requirements of Entry
Normally a grade D3 or above in Financial Accounting 1 or equivalent.
Excluded Courses
None.
Co-requisites
None.
Assessment
Assessment
Are reassessment opportunities available for all summative assessments? No
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. Normally, the group-based assessment listed above cannot be reassessed.
Course Aims
The aim of this course is to develop general decision-making and problem-solving skills using data analytics methods and tools in the accounting and audit context.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Set relevant business questions that can be addressed using data.
2. Evaluate the data quality and tools.
3. Create appropriate models using supervised and unsupervised approaches.
4. Utilise predictive analysis for financial accounting, management accounting, and auditing tasks.
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.