Objectives and competences
In the course, the student systematically acquires knowledge in the field of data analytics, which is related to performing activities in the field of accounting and auditing, especially for business decision-making needs. It is knowledge about the use and usefulness of data analytics in the field of accounting in various organizations.
Content (Syllabus outline)
• Data analytics for accounting and identification of problems
• Pre-processing data, performing tests and analysing the results
• Communication and visualisation of results
• The modern accounting environment
• Financial statements analytics
• Managerial analytics
• Audit data analytics
Learning and teaching methods
Lectures and discussions in the classroom. Studying examples and solving tasks, including discussion. Independent study of the student.
Intended learning outcomes - knowledge and understanding
Students:
Knowledge and understanding:
• Gain an understanding of knowledge in the interdisciplinary field of accounting and data analytics and related fields.
• They are aware of dilemmas related to data analytics, accounting and data.
• They know and understand various methods and techniques applicable to their work.
Intended learning outcomes - transferable/key skills and other attributes
Cognitive/Intellectual skills:
• They know how to critically examine simple and complex problems in assignments and choose the appropriate way to solve them.
• They know how to identify and examine a problem from several various perspectives and synthesize information.
• They know how to solve problems independently and in an original way in practice.
Key/Transferable skills:
• They develop skills and abilities to independently use data analytics in accounting and auditing, connecting different concepts.
• They develop the skill of explaining assigned tasks in the field of data analytics to others.
• They acquire the skills and abilities to select and manage data with minimal guidance.
• They develop the ability to evaluate their performance and the performance of others.
Practical skills:
• They acquire practical and technical knowledge regarding the pre-processing of data from the accounting field, their further processing and analysis.
• They acquire practical knowledge about the formation and use of information from the field of accounting, including the use or development of new procedures in changed circumstances, which enables them to work independently.
Readings
• Guide to Audit Data Analytics. (2018). AICPA.
Dodatni viri/Additional Readings
• Vernon Richardson, Ryan Teeter, Katie Terrell. (2023). Data Analytics for Accounting, 3rd Edition. McGraw Hill.
• Ann C. Dzuranin, Guido Geerts, Margarita Lenk. (2022). Data and Analytics in Accounting: An Integrated Approach, 1st Edition. Wiley.
• Tarek Rana, Jan Svanberg, Peter Öhman, Alan Lowe (2023). Handbook of Big Data and Analytics in Accounting and Auditing. Springer.
• Jim Lindell. (2020). Analytics and Big Data for Accountants, 2nd Edition. AICPA.
Additional information on implementation and assessment Written exam.
