Business Analytics MSc – 2022 entry

In our fast-paced, data-driven modern world, business analysts help organisations turn big data into big ideas. Artificial intelligence, machine learning and management science power decisions in business. You’ll gain data-led insights and optimise businesses by using descriptive, predictive and prescriptive analytics.

Our highly practical MSc Business Analytics course will transform you into a confident lateral thinker who is up-to-date on the latest theory and practice. While you benefit from the input of inspiring industry experts, in class and on-site, we will also make sure you’re immersed in the business problems faced by the global business community today.

We are ranked in the top 10 for business and economics in the UK by the Times Higher Education World University Rankings 2020.

Learn how to become a business-oriented data scientist

This course aims to take your analytics career to the next level and develop your ability to support and make decisions using big data confidently. You’ll learn and apply a range of techniques and tools to analyse data related to a range of diverse business operations contexts.

Develop analytical skills employers seek

You’ll gain a deep and thorough understanding of quantitative analytical methodologies and learn through hands-on experience with a range of decision-making software and data management tools.

Develop problem-solving skills

Your studies will focus on two major areas: analysing business data and using data to solve business challenges. On this course, you’ll learn how to apply new knowledge and demonstrate your skills prowess through practical problem-solving challenges.

Learn how to become a critical thinker

You’ll gain the ability to independently evaluate critical approaches and techniques relevant to business analytics. You'll learn how to relate existing knowledge structures and methodologies to analytical business challenges.

Learn how to manage analytics projects

You'll master the skill of running data analytics projects, from assessing and analysing raw data to preparing visualisations, and concluding by optimally communicating your results effectively to a select audience.

Our course runs over three semesters. You'll take four modules in both Semester 1 (October to January) and Semester 2 (February to June). Semester 3 runs from June to September. You’ll carry out your independent project (dissertation) during this time.

Students who start in February will take four modules in Semester 1, two compulsory modules in Semester 2 and two optional modules in the Semester 3. For February students, Semester 2 starts in June/July of the first year, and Semester 3 starts in October of the following academic year. You’ll also carry out your independent project (dissertation) during this time.

Modules listed are indicative, reflecting the information available at the time of publication. Please note that modules may be subject to teaching availability, student demand and/or class size caps. 

Important: In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.

We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2022/23 This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.

The University operates a credit framework for all taught programmes based on a 15-credit tariff. Modules can be either 15, 30, 45, 75 and 120 credits, and additionally for some masters dissertations, 90 credits.

The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:

New students will receive their personalised timetable in Welcome Week, and in subsequent semesters, two weeks prior to the start of semester. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day of the week (Monday–Friday). Wednesday afternoons are normally reserved for sports and cultural activities. Part-time classes are normally scheduled on one or two days per week, details of which can be obtained from the Academic Hive. View our Timetabling Policy (PDF).

Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.