Business Analytics

Entry requirements

You will typically need an upper second-class honours degree or an international equivalent in a quantitative degrees (including Accounting and Finance, Actuarial Sciences, Computer Science, Data Science, Economics, Engineering, Finance, International Economics and Trade, Maths, Physics, Commerce (with specialism in Accounting/Finance/Accounting and Finance/Economics).

OR

An upper second-class honours degree or international equivalent in any discipline (including joint degree programmes) with 2 DIFFERENT modules at 60% or equivalent from the modules in the Maths qualification requirements list below or similarly titled modules.

We will consider your application if your interim grades are currently slightly lower than the programme's entry requirements and may make you an aspirational offer. This offer would be at the standard level, so you would need to achieve the standard entry requirements by the end of your degree. Specific module requirements would still apply.

If your achieved grade is lower than our entry requirements, your application may be more likely to receive an offer if you have additional relevant work experience or qualifications. If you have at least one of the following, please include your CV (curriculum vitae / résumé) when you apply, showing:

• evidence of relevant work experience (5 years minimum) in Digital marketing, Data/Business analytics, Data Science, Data Engineering, Banking and Finance, any other work sectors/experience requiring expertise in business/data analytics/analysis and/or statistics (e.g. data analyst; human resource/people analytics; retail analytics; logistics, healthcare analytics). Policy analyst and business analyst may also be considered provided you can demonstrate the use of data analytics and/or statistics as part of your work.
• a relevant postgraduate qualification.

Months of entry

September

Course content

The MSc Business Analytics is a professionally accredited, one-year specialist programme for students aiming to master the latest techniques in descriptive, predictive, and prescriptive analytics. You develop the skills to integrate advanced data analytics with business decision-making, with the ability to bridge the gap between technical expertise and business leadership, and to collaborate effectively with decision-makers in diverse organisational contexts.

Combining rigorous analytical training with practical problem-framing and results communication, you can gain the skills to contribute to data and AI-driven innovation, supporting transformative solutions across competitive industries.

Accredited by the Institute of Analytics (IoA), MSc Business Analytics emphasises professional and ethical standards while enhancing employability. Designed with industry insights from leading organisations such as IBM, NHS, Amazon, and Barilla Group, and enriched by alumni feedback, it delivers a cutting-edge education.

To build analytical expertise and career readiness, the programme offers opportunities to work with the Professional Liaison Network (PLN) on consulting projects, providing hands-on experience with organisations. You'll work on real-world challenges with partners like Barilla, Yeo Valley, Financial Times, IBM, and Bristol Airport. Projects cover topics such as resource allocation, people analytics, customer segmentation, performance measurement, healthcare workforce analysis, and renewable energy systems automation.

You'll also gain experience with a range of decision-support tools such as:

• Python
• R
• MS Excel
• Tableau for data visualisation
• Lingo for ad-hoc analytics.

Alumni and industry panel discussions, guest lectures by business analytics experts from a variety of sectors, career development workshops, and technology sessions on industry tools such as PowerBI, SQL, and @RISK, are integral elements designed to keep you at the forefront of current work practices. Mentorship programmes to connect students with alumni and industry experts.

The programme covers:

• Mastering data identification, extraction, and cleaning techniques to ensure high-quality datasets.
• Applying statistical and machine learning methods for data mining and predictive analytics.
• Formulating and executing statistical and mathematical models to drive optimal business decisions.
• Visualising, interpreting, and communicating the results of statistical analyses to inform decision-making.

Benefit from our guidance to help you achieve professional accreditation from the UK's leading Operational Research Society and other affiliated organisations such as the Alliance of Data Science Professionals.

Information for international students

See international equivalent qualifications on the International Office website.

Fees and funding

The Business School is offering a range of scholarships for master's students starting in 2026.

Scholarships for International Students include Think Big Scholarships and Think Big Career Accelerator Scholarships.

Scholarships for Home (UK) Students include the Business School Advance Scholarship.

Further information on funding for prospective UK and international postgraduate students.