The MSc Business Analytics is a professionally accredited, one-year specialist programme for graduates with a bachelor's degree with a substantial quantitative component, and highly qualified graduates from other backgrounds with demonstrable advanced quantitative skills. It will suit graduates or early career professionals who wish to pursue a career in business analytics across sectors such as digital marketing, human resources, logistics, retail, finance, banking, insurance, healthcare, and agriculture.

The programme accreditation is awarded by the Institute of Analytics (IoA), which is the professional body for analytics and data science professionals across the world. Their mission aligns with our vision of developing and promoting the highest professional and ethical standards in the realm of data analytics. By becoming IoA Corporate Partners, we demonstrate our commitment to staying up to date in the fast-evolving field of analytics and data science. This in turn, will help to boost your employability, ensuring you are well-equipped to navigate the fast-changing landscape of analytics.

As well as benefiting from the accreditation, the MSc Business Analytics has been created in partnership with industry professionals from IBM, LV and UCL/IBM Industry Exchange Network. It provides students with the opportunity to work on business analytics projects and offer data-driven solutions to a real-life managerial decision-making problem or challenge, where possible, in partnership with IBM and other private, charity, and public sector organisations.

Students will gain a critical understanding of organisational, societal, and ethical issues in the use of Business Analytics. These issues are crucial for many organisations that seek to provide data-driven services while trying to balance innovation and competitiveness with public trust and corporate social responsibility. Examples of projects include optimisation of resource allocation, people analytics to support hiring decisions, sales forecasting, performance measurement and evaluation, customer segmentation, and sentiment analysis to improve a business strategic direction.

At the end of the programme, students will have learned:

  • technical skills in data preparation (such as identification, extraction, and cleaning of data);
  • the use of statistical and machine learning techniques to perform data mining and predictive analytics;
  • the formulation and execution of statistical and mathematical models to optimise challenging business decisions;
  • the visualisation, interpretation, and reporting/communication of results from statistical analysis.

Students will learn how to perform ad-hoc data analytics in Python and through specialised software and decision support platforms such as Lingo. They will also be offered guidance on how to successfully receive professional accreditation from the UK’s Operational Research (OR) Society as well as other affiliated organisations such as the Alliance of Data Science Professionals.

You will be taught by leading academics whose research tackles the major issues in business analytics. 88% of our Business and Management research is rated as world-leading or internationally excellent (REF 2021), reflecting its impact on shaping policy and practice. Bristol is a vibrant, ambitious, and entrepreneurial city and home to SETSquared, the world's top university business incubator (UBI Global).

Programme structure

Successful completion of five core units, two optional units, and a final applied research project lead to an MSc Business Analytics award.

The core units in the first term will provide students with the foundations in descriptive, predictive, and prescriptive analytics. You will learn skills in Python, data preparation, application of statistical models and machine learning, data visualisation to gain business insights, decision-making and optimisation for complex business processes, across a range of business areas (for example, marketing, people analytics, project analytics, financial portfolio optimisation, productivity analysis).

Depending on which elective you choose in the second term, you will have the opportunity to advance your knowledge and skills in social media and web analytics (such as social network analysis, Natural Language Processing, sentiment analysis), or optimisation (algorithms for solving large-scale optimisation models), or learn theory and practice of decision-making in business analytics (heuristics and biases in managerial judgment), or consult on a real-life business analytics project, where possible, with external industry partners.

Across the two teaching blocks, students will learn about ethics and sustainability issues in the adoption of business analytics. After learning research methods, students will have to complete an Applied Research Project in Business Analytics, which may be conducted in partnership with external organisations and will be assessed with a dissertation.

Visit our programme catalogue for full details of the structure and unit content for our MSc in Business Analytics.

Entry requirements

An upper second-class undergraduate honours degree or international equivalent in any of the following subjects:

Operational Research, Management Science, Decision science, Mathematics, Statistics, Data Science, Finance (not Accounting and Finance), Economics, Computer Science, Physics, Engineering, Biomedical/Life Sciences.


An upper second-class honours degree or international equivalent in any discipline that includes 65% or above in at least 2 quantitative units. Examples of acceptable units include:

Advanced Maths/ Algebra /Analysis /Bayesian Modelling /Calculus /Complex Functions /Decision Maths /Differential Equations / Ordinary Differential Equations /Discrete Mathematics /Econometrics /Financial Maths /Game Theory /Geometry /Information Theory /Kinematics /Kinetics /Quantum mechanics /Quantum computing /Linear Algebra /Linear Programming /Macroeconomics / Economics III / IV) /System dynamics /Thermodynamics /Complex systems/equilibrium /Mathematical Programming /Maths/mathematical methods/mathematical models/mathematical skills /Maths for Business / Business Maths /Maths for Economics /Mechanics (any type of mechanics) /Microeconomics (inc intermediate / advanced)/ Economics III / IV) /Multi Variate Analysis /Network Science /Number Theory /Optimisation /Probability (including stochastic models/methods (e.g. Markov chain model, monte carlo models)) /Proof / Intro to Proof /Pure Maths /Quantitative Methods /Statistics/Statistical Methods/Statistical Analysis etc /Time Series Analysis /Forecasting / Physics/Physical computing /Electronic/electrical engineering /Electricity and magnetism /Engineering materials /Geotechnical /materials/structural engineering /Analytical chemistry /Simulation /Probability /Computer Science (incl programming/algorithms) /Mechatronics /Data Mining/Data Science/ Data Analytics/business analytics /Management Science /Decision Analysis and Simulation; decision science /Operational research /Derivatives /Econometrics /Financial Modelling /Quantitative techniques (intro/ advanced) /Quantitative Methods /Quantitative Research Methods /Statistics/Statistical Methods/Statistical Analysis etc /Social network analysis /Computational research methods in the social sciences /Any computational methods /Machine learning /Robotics /Experiment (e.g. experimental design, studies or research; control trials) /Research methods in health/medical/biomedical/natural sciences.

For applicants who are currently completing a degree, we understand that their final grade may be higher than the interim grades or module/unit grades they achieve during their studies.

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

We will consider applicants whose grades are slightly lower than the programme's entry requirements, if they have at least one of the following:

  • evidence of significant (minimum of 6 months in a paid role) relevant work experience in sectors such as Digital Marketing, Data Science, Data Engineering, Banking and Finance or roles which require expertise in data analytics or statistics.
  • a relevant postgraduate qualification.

If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.

See international equivalent qualifications on the International Office website.

Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.

Go to admissions statement

If English is not your first language, you will need to reach the requirements outlined in our profile level B.

Further information about English language requirements and profile levels.

Fees and funding

UK: full-time
£18,100 per year
Overseas: full-time
£34,000 per year

Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.

More about tuition fees, living costs and financial support.

Alumni discount

University of Bristol students and graduates can benefit from a 25% reduction in tuition fees for postgraduate study. Check your eligibility for an alumni discount.

Funding for 2024/25

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

Career prospects

The MSc Business Analytics Programme responds to the increasing demand for skills in business analytics both in the UK and abroad.

Our Careers Service offers support and online training to help you identify your career goals, apply for opportunities in professional settings, and perfect your interview technique during your year of study.

Career paths examples include:

  • Business Analytics Specialist/Professionals
  • Management Consultant
  • Product Manager
  • Market Research Analyst/Digital Marketing
  • Operations/Data Analyst
  • Modelling/Data Scientist
  • Business Operations Analytics Specialist
  • HR/People/Insurance Analytics Specialist
  • Financial Analyst.