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Our MSc Business Analytics covers a range of topics essential for understanding and leveraging data in business contexts. You will graduate with strong theoretical and practical knowledge of:

• Data analytics and visualisation - learning how to analyse and visualise data using tools like Python or R.
• Big data technologies – gaining understanding of the technologies that enable the management and analysis of large datasets.
• Soft systems methodology – exploring methodologies for addressing complex business problems involving multiple stakeholders.
• Business fundamentals – covering the core tenets of business and management such as finance and strategy for managers.
• Contemporary issues for business and society - learning about key challenges that business and society face and refining your critical insight, preparing you to become a successful business analytics leader in our fast-changing, global ecosystem.
• Consulting and project management - developing skills in managing projects and consulting within business analytics contexts.

Additionally, you will:

• Experience the benefits of your ‘Capstone’ choice – you will have a choice between three ‘Capstone’ options, including (1) creating your own business, (2) consulting for a real business on a high-level problem, or (3) undertaking your own specialised research dissertation. Each of these options is designed to build your skills, knowledge, and employability.
• Build your confidence – you will develop and nurture your confidence, as well as your decision-making abilities.
• Receive the optimum balance of theory and practice - you will gain an excellent academic underpinning  along with opportunities to develop real-life, practical experience, giving you an employability edge upon graduation.
• Work with real clients and professional mentors, which provides a fantastic opportunity to put learning into practice and build skills that will last a lifetime.

Structure and exit awards

MSc (250 credits). Alternatively, you may like to consider theÌýMSc Business AnalyticsÌý(185 credits) route that does not include professional practice and is available both full time or part time.

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Teaching, learning and assessment

Teaching comprises a combination of face-to-face tutor-led seminars, tutorials, case studies, field trips, projects and online directed learning as part of a blended learning approach. The 'capstone' module for the courseÌýis either a 'live' project for a client, the development of a business start-up proposal, or a master's research dissertation. Each of these options is intended to draw together elements of the taught course. The dissertation or project will be facilitated, monitored and assessed by tutors within QMU and, where appropriate, by staff within the organisation in which it is undertaken.

Assessment will take a variety of forms, including infographics, dashboards, reports, group and individual presentations. In our assessment methods, we have a particular focus on enabling you to demonstrate practical skills development, along with theory, making you particularly attractive to potential employers.

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Teaching hours and attendance

If you are studying full-time, teaching normally takes place over two or three days mid-week, comprising both classroom-based learning and industry learning. You will also be required to carry out independent learning to support your formal teaching. Your specific timetable will depend on whether you are studying full-time, part-time or an individual module. Learning time varies across modules. Timetables are normally available approximately one month before you commence your studies.

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Class sizes

There are normally around 20-30 students. Sometimes, you may have lectures with additional students on other courses who are studying the same modules.

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Teaching staff

You can read more about the teaching staff on this course at the bottom of this page. Please note that teaching staff is subject to change.

You will study the following modules:

• Data Analytics for Management Decision-Making (15 credits): This module explores the sources of data, how that data is collected, processed, and presented, and then continues the data lifecycle by considering how this is used within informed decision-making processes within contemporary enterprises. With so much data noise, how can a business be certain that the data they are using is reliable and valid? How can they then link that to a primary function within management and leadership when making decisions?Ìý
• Statistics and Analytics for Data Visualisation in Business (15 credits): In this module, you will explore data and the questions it can answer. Using existing datasets, you will develop research questions, describe variables and relationships, calculate basic statistics, and present results clearly. You’ll gain a robust quantitative foundation, practical problem-solving techniques, and knowledge in data analysis for business problems. The module covers handling data programmatically without being software engineers, using state-of-the-art software for visualising, investigating, and sharing large datasets, including dealing with missing data, variable groups, and graphs.
• Systems Analytics and Data Architecture (15 credits): This module provides a strategic view of business information systems and their data structures to support analytics and business re-engineering. It covers methods for analysing and designing information systems using object-oriented methods. Students will learn about the system development lifecycle, professional standards, and roles at each stage. The module includes specifying system requirements and using systems analysis and design techniques to solve business information system problems. Additionally, students will apply object-oriented approaches, such as Unified Modelling Language (UML), to develop complex information systems projects.
• Business Forecasting and Data Modelling (15 credits): Business forecasting and data modelling are essential in business analytics. This module covers forecasting, predictive analytics, and data modelling, employing various methodologies to meet evolving business needs. You’ll learn to distinguish true signals from noise, perform forecasting using time-based data, and apply techniques like regression, classification, clustering, Bayesian, and machine learning. Practical exercises will help you solve common business problems and assess solution effectiveness. Ethical considerations and limitations of predictive models are also explored.
• Contemporary Issues in Business and Society (15 credits): This module aims to enable you to reach a well-grounded understanding of the theory and practice of international management and relate it to events taking place at a global and national level. Utilising the United Nations Sustainable Development Goals as a discursive element within the module, the ways in which businesses can positively contribute to achieving these will be critically evaluated. This module also explores what it is to be a master's student so that all students enrolled onto the course can access this higher level of postgraduate education in an effective manner.Ìý
• Finance for Management (15 credits): This module develops your critical understanding of essential management accounting and finance topics within a business environment, enabling you to develop a high-level understanding of how financial information helps to make informed and accurate management decisions. This module is CIMA accredited.Ìý
• Strategic Management (15 credits): This module concerns itself with assessing what’s important, determining how to get there, and avoiding the potential pitfalls. By focusing on long-term sustainable success, strategic management enables practitioners to avoid the noise of the day-to-day. The module incorporates strategic concepts, tools and techniques that organisations can employ to assess their environment and resources and make strategic decisions towards long-term success. This is a mandatory module for all Queen Margaret Business School MSc courses. Much of the knowledge and skills developed in this module are transferrable and useful in a broad range of management functions.
• Research Methods Problems and Solutions (20 credits): Research has an important role within academic studies but is also a core skill for managers and leaders within contemporary enterprises. This module is designed to develop both theoretical research knowledge, and practical insights into the purpose, nature, execution, and value of research approaches and how these can be effectively utilised in the solving of problems in the context of academic knowledge creation or organisational professional practice.
• Professional Practice Internship (60 credits): Upon completion of the taught courses above, you will also undertake an internship in an area where you plan to develop your career. Working with the Internship team, you will source and develop an internship in partnership with both the internship provider and the university. Within your internship you will be working towards the attainment of the internship learning aim and outcomes that you have set, and your will reflect upon your experience for your assessment. The internship experience is supported by an academic internship specialist and there is a taught programme that supports all students through this process.Ìý
• Dissertation (60 credits): In addition to the Internship, you will also complete a 12,000-word Dissertation after the internship programme has been completed. It will enable you to develop, plan and critically evaluate a piece of research in the relevant degree subject related area, written up in the form of a dissertation. This offers the opportunity to conduct a substantial academic research project around a research topic of your choice.

NB The modules listed are correct at time of posting (October 2024) but are subject to change. In the event that modules change, QMU will seek to use reasonable endeavours to ensure that there is no detrimental impact on students.

Graduates of the MSc Business Analytics will be well equipped for a variety of roles, including:

• Business Analyst
• Data Analyst
• Business Insight Manager
• Management Information Systems (MIS) Specialist
• Management Decision Systems (MDS) Specialist
• Business Consultant

Entry requirements

Applicants should have a UK honours degree or an overseas qualification of an equivalent standard in an appropriate discipline. We also welcome applicants with an ordinary degree who can show a period of relevant post-graduation work experience in a managerial role.

International: You will be required to provide evidence of English language competence at no less than IELTS 6.5 with no individual component score less than 6.0.

Accreditation of prior learning: You may be granted exemption from studying a module or modules up to a maximum of 60 credit points, provided you can demonstrate successful achievement of all the learning outcomes.

Other information

Fees for this course are calibrated to incorporate all transport and activities on field trips as well as practical classes. View our Fees and Charges page for more information.

Disability/health conditions

If you have a disability, long-term physical or mental health condition, or learning disability, it should not stand in the way of your studying at QMU. However, if you are not sure whether your disability might be a barrier in your studies or in relation to the professional standards, please contact the disability service who will be able to have a conversation with you about reasonable adjustments and supports available to you.

Applying for this course

For more information on applying, or to apply for this course, please follow the links in the 'Start your application' box at the top right of this page.

Application deadline

51ÂÒÂ×»»ÆÞ: End of August for September 2025 start and end of December for January 2026 start.

International: 26 July for September 2025 start and end of November for January 2026 start.

Please note applications may close sooner should the course become full.

Terms and Conditions

The delivery of this course is subject to the terms and conditions set out in our 2025/26 Entry - Terms and Conditions (Postgraduate).

Contact Thomas Peschken-HoltÌý(Programme Leader) orÌýcontact Admissions

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