Postgraduate Programme and Module Handbook 2025-2026
Module ACCT42415: Introduction to Data Analytics & Visualisation
Department: Accounting
ACCT42415: Introduction to Data Analytics & Visualisation
Type | Tied | Level | 4 | Credits | 15 | Availability | Available in 2025/2026 | Module Cap | None. |
---|
Tied to | L1T509 |
---|---|
Tied to | L1T709 |
Tied to | L1T712 |
Tied to | L1T714 |
Tied to | N4R201 |
Prerequisites
- None
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- 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.
Content
- The fundamentals of data analytics.
- Descriptive data analytics techniques.
- Data visualisation.
- Predictive data analytics.
- Prescriptive data analytics.
Learning Outcomes
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.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- 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.
Teaching Methods and Learning Hours
Activity | Number | Frequency | Duration | Total/Hours | |
---|---|---|---|---|---|
Online Learning Activities | 90 | ||||
Independent Study | 60 | ||||
Total | 150 |
Summative Assessment
Component: Individual assignment | Component Weighting: 90% | ||
---|---|---|---|
Element | Length / duration | Element Weighting | Resit Opportunity |
Assignment | 2500 words max or equivalent | 100% | |
Component: Peer assessment | Component Weighting: 10% | ||
Element | Length / duration | Element Weighting | Resit Opportunity |
Exercise | Ongoing throughout module | 100% |
Formative Assessment:
Students undertake a series of activities aligned to the module content, receiving ongoing feedback on the theoretical knowledge and how it is applied.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University