MSc Business Analytics
Please note: This page is for 2027 entry. Click here for 2026 entry.
| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time |
| Entry year | 2026 + January 2027 start |
| Campus | Streatham Campus |
| Typical offer | A 2:2 or equivalent |
|---|---|
Why study MSc Business Analytics at Exeter?
- Become skilled in supporting managers to make data driven decisions about the daily running of a business through analysis of data from social media and marketing as well as using techniques in optimisation and forecasting.
- This flexible programme with strong theoretical foundations suits those looking for a career in business analytics as well as those wishing to go on to study a PhD.
- The basis of our course ensures you have an excellent understanding of business analytics, basic programming and mathematics skills alongside expertise in presenting and communicating data to managers.
- You can choose from modules in areas such as Marketing Analytics, Strategic & HR Analytics, Operations Analytics, and Environmental Analytics enabling you to curate a degree that supports your career aspirations.
- Your employability skills will be enhanced throughout the programme, finishing with a Business Project module using real data to address a real organisational problem.
- High achieving students have the opportunity to apply for the Quantitative Techniques for Economics and Management (QTEM) programme which includes an internship and semester abroad.
Fast Track (current Exeter students)
Master your future in Management at the University of Exeter.
26th for diversity and top 90 for employability globally for Business Analytics
QS Business Master’s Rankings 2025
Triple accredited Business School
AMBA, AACSB, EQUIS
Spend an additional semester studying at one of the prestigious academic partners with our QTEM Programme
Top 10 in the UK for Business, Management and Marketing
9th in The Times and The Sunday Times Good University Guide 2025 and 8th in the Complete University Guide 2027
Studying Business Analytics opened so many new horizons for me. When I began the course, I had no prior knowledge of coding, but the University offered numerous free workshops to learn programming languages.
Amna
MSc Business Analytics graduate
Entry requirements
A 2:2 or equivalent from a recognised university, including at least one mathematical / quantitative module at 2:2 or equivalent.
We do consider all applications where there is evidence of exceptional performance in modules relevant to the programme of study, significant relevant work experience or professional qualifications.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course.
The required IELTS test scores for this course fall under Profile B1.
Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
The MSc Business Analytics programme is for you if you are interested in a career related to business analytics or you wish to study a related PhD. You will learn how to support managers to make data driven decisions using a variety of techniques.
Our core modules provide an excellent foundation in business analytics, basic programming and mathematical skills, as well as techniques to present and communicate data to managers. Our choice of optional modules ensure you can flex the programme to suit your interests and career or research aspirations.
Our Business Analytics programme is inspired by global challenges and draws upon the University of Exeter’s world-leading environmental research. There are increasing pressures on business to manage and report climate exposure in their supply chain and investment portfolios, mitigate risk of climate change and natural hazards on their operations, and manage their wider environmental impacts. You will learn about these challenges, and how business analytics approaches can support businesses in overcoming them.
You will complete a research project (Business Project) supervised by an academic from the Business and Management department. Your project will be based around a sizeable business problem that draws upon your newly developed business analytics skills.
The programme is delivered over three terms and is University-based throughout this time.
The taught components of the programme are delivered in the first two terms, leaving the third term to complete your Business Project. The programme runs from September to September or January to January depending on your chosen start month.
Please note that the module information displayed here is subject to change.
- During the programme you will study modules totalling 180 credits.
- Please note that programme structures may be subject to change.
120 credits of compulsory modules, 60 credits of optional modules
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| Compulsory 1 | ||
| Topics in Business Analytics | 15 | |
| Programming for Business Analytics | 15 | |
| Database Technologies for Business Analytics | 15 | |
| Statistics and Mathematics for Business Analytics | 15 | |
| Analytics and Visualisation for Managers and Consultants | 15 | |
| MSc Project | 45 | |
BEMM457: Topics in Business Analytics
This module introduces key concepts and contemporary topics in business analytics and data-driven decision-making. It provides a foundation for understanding how organisations leverage data to enhance performance, improve strategic positioning, and create value across customers, employees, and operational processes.
Students will engage with a range of complementary analytics topics, including data visualisation, descriptive and diagnostic analytics, and introductory predictive approaches. The module emphasises the practical application of analytics through hands-on experience with industry-relevant software such as Tableau, Power BI, Google Analytics, and SPSS, enabling students to develop both technical and analytical capabilities.
In addition, the module introduces emerging developments in analytics, including the role of Artificial Intelligence (AI) and Large Language Models (LLMs) in transforming business decision-making and data interpretation. Students will explore how AI-driven tools can augment analytical processes and enable actionable insights.
BEMM458: Programming for Business Analytics
In this module, you will learn fundamental programming skills that enable you to search and sort data. You will be introduced to programming in Python and will learn how to develop and run programmes in Jupyter Notebooks. You will learn key programming principles and will practice applying them to real business problems. These skills will form the basis of your ability to address business problems using data.
This module aims to provide a comprehensive introduction to the programming skills underpinning Business Analytics and Data Science.
You will learn to:
- Understand the role that programming plays in a Business Analytics context
- Be confident writing, testing and debugging procedural and functional programmes in Python
- Import and process data using Python
- Understand the principles of object-oriented programming for Python
BEMM459: Database Technologies for Business Analytics
In this module you will learn the basics of database design and how to manage data. You will learn how to use Python to access, manipulate and store data. You will develop a theoretical understanding of relational databases (RDBMS) and NoSQL databases. You will gain practical experience of using Structured Query Language (SQL), using python libraries for data access and data storage.
This module aims to equip you with both the theoretical knowledge and the practical skills required to:
(a) Design and implement a relational database (Entity-Relationship diagrams, normalisation);
(b) Use Data Query Language with relational databases - data definition language (DDL), data manipulation language (DML) and structured query language (SQL);
(c) Design and implement a NoSQL (non-relational) database (Redis , MongoDB , Neo4j);
(d) Use Python libraries to access relational databases and NoSQL databases.
BEMM460: Statistics and Mathematics for Business Analytics
This module will cover a range of mathematical methods that are used in business analytics, including key principles in statistics, econometrics, probability and algebra. These will form the foundation of analytical methods that you will explore and apply in later modules.
The module aims to enhance your ability to understand the math and statistics behind analysing a business problem. You will be able to observe and interpret mathematical concepts in business and economics literature as well as to prepare a business/consulting report with the appropriate mathematical and statistical techniques.
The module runs in the Autumn term for September starters and in the Spring term for January starters.
BEMM461: Analytics and Visualisation for Managers and Consultants
In this module you will develop the skills necessary to communicate analytical results to senior managers. You will learn the consulting skills necessary to understand business problems and develop solutions based upon analytics. The module will develop your skills in communicating information about data visually and verbally.You will learn how to use visualisation tools in Python.
'A good sketch is better than a long speech' - often attributed to Napoleon Bonaparte
This module focuses on the skills necessary to communicate data and results to others.
Students will learn the best practices for creating effective visualisations.
Students will be able to assess the quality of visualisation approaches.
Understand the most appropriate method of visualising a variety of data types.
Present information that facilitates decision making.
Students will deliver a presentation that critically evaluates an existing visualisation and will undertake a final project to demonstrate their visualisation skills.
BEMM828: MSc Project
You will undertake an independent research or consultancy project based upon a topic of your choice. The report will consist of 10,000 words and contain relevant analytical tables and figures. The project will allow you to demonstrate the skills you have learned during the programme. These skills include, e.g., the following: project management, operations management or supply chain analytics, project planning, visual representation, and writing. Each student will be supported throughout the project by an advisor or supervisor.
The supervised project represents the culmination of all PG programmes of the Operations and Analytics department, where you either develop a theme as provided by an academic member of staff, or you can decide on a topic yourself. This provides you with the opportunity to apply concepts or challenges from real-world settings. Primary research collection during this period (e.g., service/production data, interviews), is encouraged, including contact with organisations who may require specific assistance.
Optional modules
| Code | Module | Credits |
|---|---|---|
| Optional 1 | ||
| Entrepreneurship: New Venture Creation | 15 | |
| Operations Analytics | 15 | |
| Marketing Analytics | 15 | |
| Strategic and HR Analytics | 15 | |
| Environmental Analytics | 15 | |
| Design Intelligence | 15 | |
| Supply Chain Analytics | 15 | |
| Programming for Prompt Engineering | 15 | |
| Machine Learning for Social Data Science | 15 | |
BEMM394: Entrepreneurship: New Venture Creation
This module introduces both the theoretical and practical aspects of entrepreneurship and new venture creation. It adopts various perspectives to provide a holistic picture of the entrepreneurial process, including, but not limited to, the practical aspects of the intellectual, behavioral, and emotional demands of starting a new venture. The module is intended to provide rigorous insight into the realities of entrepreneurial activity and an understanding of the role that small and medium-sized businesses play in the modern economy. This may be achieved by creating a new independent firm or organizing a new enterprise within an existing firm.
If you already have an idea for a new business or are working on one, this module offers an opportunity to develop, refine, and test it.
Additional Information:
Internationalisation
You will have the opportunity to develop the ability to think globally and understand international cultures through working on global sustainability problems with classmates from diverse cultures. Diverse teams enable understanding of global problems from multiple perspectives and the development of viable solutions.
External Engagement
This module draws on academic and entrepreneurial experts to enrich your learning journey.
Sustainability
You are encouraged to tackle sustainability-related issues in your group activities and individual assignments.
Employability
BEMM462: Operations Analytics
This module focuses on analytics from an operations management perspective. Operations Management covers the design, optimisation and management of products, processes, services and supply chains. It uses analytics to make decisions regarding product and service quality and cost, and as well as decisions regarding acquisition, development, and utilization of resources. You will learn about the value of analytics when applied to different types of data such as: machine data, sensor data, and other forms of data generated by operational systems.
The module aims to impart knowledge and skills in optimisation and decision-making algorithms where students can apply to a variety of fields, including business, education, and research. Graduates of this module would be equipped to frame and analyse decisions through an optimisation framework, leading to employment as technical staff members in business or industry, government planners, and private consultants.
BEMM463: Marketing Analytics
This module covers knowledge and analytical skills that marketing professionals need to deploy to understand the marketing environment (e.g., customers and competitors) and to make strategic marketing decisions. You will learn how to use a systematic and analytical approach to marketing decision-making and to measure the performance and effectiveness of marketing initiatives (e.g., advertisements, new product development). The module will cover different ways to collect data and the statistical techniques that can be used to analyse the data.
This module aims to enable you to:
- Develop knowledge and understanding of core marketing principles - including concepts and theories associated with customers, products and services, and competitors;
- Learn about statistical, analytical and data science techniques and their application to marketing;
- Develop knowledge of how analytical techniques can inform design and implementation of marketing strategy, and improve marketing decisions.
BEMM464: Strategic and HR Analytics
In this module you will deepen your understanding of how to identify and analyse data and information essential to making strategic and HR decisions. In addition to introducing various concepts, theories and frameworks from strategic management and human resources management that can be used to help identify and evaluate important sources of data and information relevant to key strategic and HR decisions and leverage points, the module will develop understanding about how unstructured text can be converted to structured data and then analysed using various dimension reduction techniques. Key concepts taught include pattern recognition, classification, categorisation, and concept acquisition. Additionally, the module will also cover recent developments in the field such as machine learning, deep learning and neural networks and their role in the analytics toolkit.
BEMM465: Environmental Analytics
This module will cover key analytical principles that enable businesses to manage their relationship with the environment. It will include situations in which the environment impacts upon business, such as natural hazard risk management and managing natural resources in the supply chain for renewable energy and food; and situations in which businesses impact upon the environment - such as managing carbon emissions and waste management. You will learn about key environmental datasets, including their structure, uncertainties and sources, and techniques for using these datasets to create actionable intelligence for businesses.
There are increasing pressures for businesses to better understand their interactions with the environment.
This module aims to equip you with the knowledge and skills required to understand:
- The key ways in which businesses impact the environment
- The key ways in which the environment impacts businesses
- Key topics in environmental corporate responsibility
- How environmental data and analytics can support businesses in managing their interaction with the environment
BEMM486: Design Intelligence
Industry 4.0 and the advances of digital technologies offers the opportunity to develop data-driven products, services, and business. The module brings together creative methods and design thinking approaches to apply digital technologies to address societal or business challenges. The module will develop thinking to bridge data to the context, for example transforming data intelligence to market opportunities or societal challenges informing the design of new product/ service/business concepts. The module will introduce concept generation techniques and understanding and designing stakeholder experiences. Students will work in multi-disciplinary teams across Business and Engineering.
This module will be taught in a number of block teaching sessions during the term. Dates will be confirmed for students following each term’s timetabling process.
The module focuses upon the front end of the innovation process with technological advances as an opportunity for innovation of product/service/business in response to addressing a societal or business challenge. The module provides an introduction to applying design thinking considering the opportunities disruptive technologies bring and also their implications to real world problems. We will follow a design process with guided creative sessions providing opportunities to applying a number of methods and theories to develop concepts through independent learning to a brief.
BEMM783: Supply Chain Analytics
The dynamic and economic performance of supply chains is driven by their lead-times, forecasting, and production activities. Poorly managed supply chains result in an expensive dynamic effect called the bullwhip effect. The bullwhip effect causes inefficiencies in terms of increased inventory holding and costs, poor customer service levels, and the inefficient use of production capacity. We will cover a wide range of topics, such as: Dynamic value stream mapping and time series analysis; Understanding your supply chain in relation to inventory, service levels, and capacity costs; Forecasting for production and distribution in supply chains; Setting the cadence of your production pacemaker; Detailed scheduling at the shop floor; Communicating replenishment orders with suppliers.
This module is suitable for non-specialist and interdisciplinary students. Although this module is based on real world applications of research, no industrial experience or high-level maths is required (although some basic mathematical and computer skills, mostly Excel-based, are required).
Those who are able to successfully apply this knowledge in practice will allow companies to reduce over-time working, reduce inventory investments and improve customer service levels. They will be able to create a stable working environment in supply chains so that companies have the time to undertake maintenance activities, creating a virtuous cycle of improvement.
COM2019: Programming for Prompt Engineering
Prompt engineering is the art and science of interacting with large language models. These models are increasingly important in computer science and is being rolled out into applications. In this module you will program in Python to access both public large language modules, such as GPT-4, and local language models. To undertake this module you need to have some experience of using language models (through a chat interface) and of basic programming.
This model aims to give you skills to programmatically access the contents of large language models, using the Python language. This will allow you to batch process texts and/or images to undertake tasks across a range of applications. These might include, for example, sentiment analysis, text/image classification, text summarisation. It also allows you to undertake studies of language models by probing their behaviours in an experimental manner.hat do lecturers hope to cover in this module in terms of knowledge and learning opportunities for the students? Include details of research-enriched learning/ teaching and links to employment.
SSIM916: Machine Learning for Social Data Science
Effective analytics in the era of 'big data' requires researchers to have a wide range of tools at their disposal. This module focuses a set of tools that are essential for applied and academic social data scientists: machine learning methods for structured and unstructured data. This module provides a practical introduction to the ways in which machine learning methods are applied regression problems, classification tasks, and unsupervised clustering of large datasets.
Although there are no formal pre-requisites for taking the module, some (even limited) programming experience will be helpful. You will use the Python programming language to implement most of the tools introduced throughout the term. No prior knowledge of Python is assumed. You are encouraged to reach out to module convener with questions regarding Python or programming more generally.
Fees
2026/27 entry (including January 2027 entry)
UK fees per year:
£18,600 full-time
International fees per year:
£31,000 full-time
Scholarships for January start
Our Exeter Excellence Scholarships are also available for applicants looking to study with us in January 2027 and applications for these scholarships will open in September.
Scholarships
The University of Exeter offers a wide range of scholarships to support your education, with £7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
University of Exeter Alumni Scholarship
We are pleased to offer the University of Exeter Alumni Scholarship, a scholarship for University of Exeter alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship worth 20% of the cost of your first year tuition fees.
Terms and conditions, including deadlines, apply.
It was such an honour for me to receive a scholarship award from Exeter. I felt like I had something to contribute to the university as a student, not only on an educational level, but on a professional level too.
Phuong
MSc Business Analytics
Teaching and research
Our MSc Business Analytics programme delivers a dynamic learning experience through lectures, workshops, practical sessions, practitioner insight seminars, private study, case study development, group work, individual projects, and collaboration with industry partners.
Teaching environment and support
You will benefit from the cutting-edge teaching environment and support resources at the University of Exeter Business School (UEBS), including the Centre for Innovation in Business Education. This centre fosters innovative teaching and learning practices by coordinating assessment, feedback, group work, and digital literacy projects. Staff benefit from seminars, training sessions, and an advanced Teaching Collaboratory (ELE) for online staff development, ensuring teaching excellence and a world-class student learning experience.
Your learning will be assessed through practical exercises, project work, written assignments, presentations, multiple-choice tests, and examinations. This provides a well-rounded approach to your academic and professional development.
Investment in data science and artificial intelligence
The University has invested £50 million in the development of its Data Science and Artificial Intelligence capabilities. The Accelerating Data Science and Artificial Intelligence (ADA) project has been running since 2023 and has invested in teaching, research and infrastructure which this programme benefits from.
Research environment and support
You will be taught by internationally respected academics who are at the forefront of their fields and actively contribute to UEBS's vibrant research culture. The programme is embedded within the Operations and Analytics group, a multidisciplinary team of academics from our Department of Management.
The Centre for Simulation and Analytics Management (CSAM) plays a key role in supporting research and teaching within the programme. CSAM focuses on analytical modelling and computer simulation to address real-world problems. The centre is involved in impactful projects such as:
- circular economy modelling to support sustainable production and consumption
- resilience to climate change, helping organisations adapt and thrive in uncertain environments
- urgent medical and emergency care, improving efficiency and patient outcomes using data-driven insights
The Business School's research environment has been recognised for its excellence, with 100% of our Business and Management research rated as internationally excellent in the Research Excellence Framework (REF) 2021. Read more about research at the Business School and how our academics drive innovation and sustainability across industries.
Engaging with industry and professional bodies
Our strong connections with professional organisations such as the Chartered Institute of Marketing (CIM) and the Chartered Institute of Personnel Development (CIPD) enrich our programme with industry insights, ensuring that the curriculum is aligned with professional standards and real-world needs.
Careers
Through innovative and practical learning you will have the ability to use data and analytics confidently and creatively, in order to resolve a wide range of operational and strategic problems that face global organisations across multiple sectors.
The QS Business Master's Ranking 2025: Business Analytics is made up of five Indicator Groups – within the Diversity Indicator Group our MSc Business Analytics programme ranks 26th globally and on Employability ranks top 90 globally. Our diverse student and staff population - giving you benefits in terms of networking, cultural exchanges and a more diverse learning experience - together with our strength in employability, mean that you have the support you need to get the career you are looking for.
Your future career
After graduation, you will join our community of more than 26,000 Business School alumni in over 150 different countries who are actively shaping the world around us. Graduates can look to work in a diverse range of roles including:
- Business Consultant
- Data Consultant
- Business Analyst
- Supply Chain Analyst
- Marketing Analyst
- HR Analyst
- Business Manager
Opportunities range from working in large analytics and consultancy teams within corporations in sectors such as consulting, tech and finance, through to specialist analytical roles in areas such as procurement, HR, and marketing within smaller private, public and third sector organisations. The increasing importance of analytics skills within Executive Management teams means that students will also be well placed to succeed in Graduate Management schemes.
Developing your skills and career prospects
The University of Exeter Business School provides a range of support to help you develop skills attractive to employers. Visit our postgraduate Business School careers service web page for more information.
Enhance your degree with Study Abroad opportunities
QTEM Programme*
After your first year of studies at Exeter, you can progress onto the QTEM Programme. QTEM aims to prepare students with excellent quantitative and analytical skills to support their future careers as decision makers leading the global business environment.
If you are accepted onto the QTEM Programme, you will spend an additional semester studying at one of the prestigious academic partners. This will be followed by a quantitatively focussed internship and participation in the QTEM Data Challenge which includes online data science and leadership courses as well real data analysis.
Students will be selected and nominated to QTEM by the University of Exeter Business School following a competitive internal application process. Places are limited so we recommend you register your interest before applying for your Masters.
*Open to high achieving students enrolled in the following University of Exeter Business School programmes: MSc Finance, MSc Finance and Investment, MSc Financial Economics, MSc Economics, MSc Business Analytics and MSc Marketing and Business Analytics.
For more information on QTEM and Double Degrees and other postgraduate study abroad opportunities, visit the Business School’s Study Abroad webpages.
