ACCT42415: Introduction to Data Analytics & Visualisation

• None

• None

• None

• This module will aim to introduce students to the concepts, terminologies, tools and technologies of data analytics and visualisation. In particular, on the successful completion of this module students will be able to:
• examine the evolution of data analytics including ethical issues that have arisen;
• examine the value created by data analytics in the corporate world and its applicability in business, finance, accounting and auditing;
• define and interpret the core concepts and terminologies of data analytics;
• identify the tools and technologies required for data analytics;
• critically discuss the value of data analytics to business, finance, accounting and auditing;
• explain how data analytics has been successfully used in various industries; including business, finance, accounting and auditing;
• introduce data visualisation and visual analytics;
• identify basic graphs and their use in auditing and accounting;
• examine advanced graphical presentations.

• The fundamentals of data analytics.
• Descriptive data analytics techniques.
• Data visualisation.
• Predictive data analytics.
• Prescriptive data analytics.

Subject-specific Knowledge:

• By the end of the module students should be able to show:
• demonstration of different structured and unstructured data, considering its volume, variety, veracity and velocity;
• identification of different types of data required to solve various problems and challenges using scientific assumptions and hypotheses to deal with them, from a critical perspectives;
• critical evaluation of the different business, accounting and auditing practices and the role of technologies and data analytics towards enhancing and improving these practices;
• clear understanding of data visualisation techniques;
• demonstration of advanced knowledge and understanding of the theory of data, different types of data analytics tools and techniques.

Subject-specific Skills:

• By the end of the module students should be:
• competent in data collection, data mining, data management, data coding, data classification data evaluation and data applications in business, finance, accounting and auditing;
• able to evaluate different challenges for data analytics in business, finance, accounting and auditing, such as: data ethics, confidentiality, cybersecurity, data security and fraud;
• able to visualise different data sets and extracting trends and patterns.

Key Skills:

• Data analytics and visualisation skills.
• The ability to communicate effectively: communicating complex ideas.
• The ability to think critically and creatively and to argue coherently.

• The module is delivered via online learning, divided up into study weeks with specially produced resources within each week. Resources vary according to the learning outcomes but normally include: video content, directed reading, reflective activities, opportunities for self-assessment and live scheduled webinars. The hours as depicted in the Teaching Methods and Learning Hours table are indicative.
• The formative assessment serves to encourage students to study regularly and to monitor their learning progress. Tutors provide feedback on formative work and are available for individual consultation as necessary (usually by email and Zoom or Microsoft Teams).
• The summative assessment of the module is designed to test the acquisition and articulation of knowledge and critical understanding, and skills of application and interpretation within the accounting and audit context.

Students undertake a series of activities aligned to the module content, receiving ongoing feedback on the theoretical knowledge and how it is applied.

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.