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Are you a critical thinker with the ability to analyse and interpret data?
Business Analytics is the process of predicting the needs of an organisation and analysing the effectiveness of past and present activity. This sought-after and growing business discipline is a strategic necessity for any organisation.
The MSc in Business Analytics at Kent Business School is delivered by published academics and in collaboration with industry leaders. On the course, you learn the skills, technologies, applications and practices to become an expert in interpreting and analysing enterprise data effectively.
You’ll spend Stage 1 learning business analytics topics such as advanced spreadsheets and systems, Big Data, business statistics with Python and forecasting. You will end your Master's with a detailed report, applying your expertise to a real-world scenario.
The course helped me to hone my data-handling skills and to make proper insights on data and leverage them to make decisions for a business.
~ Derek Osei Debrah, MSc Business Analytics 2020
You are more than your grades
For 2022, in response to the challenges caused by Covid-19 we will consider applicants either holding or projected a 2:2. This response is part of our flexible approach to admissions whereby we consider each student and their personal circumstances. If you have any questions, please get in touch.
A minimum of a second-class UK degree, or an equivalent internationally recognised qualification in any subject area is needed for this course. Basic quantitative skills are an advantage.
All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.
The University requires all non-native speakers of English to reach a minimum standard of proficiency in written and spoken English before beginning a postgraduate degree.
For detailed information see our English language requirements web pages.
Applicants who are required to meet an English language condition may be able to study a pre-sessional course in English for Academic Purposes through Kent International Pathways.
Duration: 1 year full-time
Our general Business Analytics programme is a flexible programme is studied over one year full-time and consists of seven compulsory and two optional modules in Stage 1. Stage 2 consisting of a piece of business analytics research.
The MSc Business Analytics programme is available with an optional industrial placement, which will require you to complete the Industrial placement Report.
The following modules are indicative of those offered on the Business Analytics programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. You may study a mix of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.
Stage 1 aims to provide you with the knowledge and understanding of business analytics covering topics such as advanced spreadsheets and systems, Big Data, business statistics with Python and forecasting.
In this module, students will learn about the fundamentals of machine learning and forecasting techniques and gain hands-on experience with analysing and solving a variety of problems encountered in business and management.
Three indicative areas of the module could include:
- Machine learning: The introduction of modern machine learning techniques used in business data analysis, including both supervised learning (e.g. regression, classification, and artificial neural networks) and unsupervised learning (e.g. association rule discovery and cluster analysis).
- Forecasting: Students will learn about various forecasting methods, including exponential smoothing methods and the Box-Jenkins method (i.e. the ARIMA model and variants).
- Data analysis report writing. Students will systematically carry out a data analysis project and write a data analysis report.
The data analysis packages such as R, SPSS, and Weka may be used in this module.
This module aims to introduce students to the power of big data analytics and data visualisation techniques in contributing to business value creation. The module will also enable students to solve a variety of complex data centred business problems using computer software tools like Apache Spark and Python.
The module covers two main themes as follows.
1. Theoretical understanding of big data analytics: This part involves learning about the theoretical foundations of big data analytics, text mining, and social media data mining. It also introduces the effective use of data visualisation and database management concepts and their links with big data analytics. Example applications of big data analytics and visualisation techniques discussed within the module will focus on addressing contemporary challenges faced by industry.
2. Building practical skills and managerial insights: In this part of the module, students will learn how to interact with both SQL and NoSQL databases and how to solve business problems using advanced functions within the Apache Spark and Python software platforms. Students will be guided through demonstrations involving a variety of exercises that will prepare them to be data-driven managers and executives capable of utilising big data analytics for business value creation.
Employers are in search for individuals who possess logical thinking, analytical capability, leadership, communication and the ability to work under pressure. This module develops the necessary research knowledge and skills for students to be able to successfully complete a piece of research in industry or consultancy contexts or academia.
Indicative topics are:
• Choosing the topic of interest and literature review
• Research process and Ethics in in business research
• Choosing your research design
• Preparing the research proposal
• Communicating the Research
The aim of this module is to enable students to use spreadsheets (Microsoft Excel) to structure, analyse and solve a variety of business problems. It will also provide the students with a basic knowledge of Visual Basic for Applications (VBA) as a means to automate Excel functionalities and create user-friendly applications.
The module will cover two main topics:
- Spreadsheet Modelling. This part will involve learning about modelling techniques to represent the real world in a structured and logical way; how to use basic and advanced spreadsheet facilities to organize, visualise, query and summarise data; how to use spreadsheets to analyse and solve managerial problems in a variety of organisations (e.g. scheduling, forecasting, inventory, optimisation, financial analysis, and project management problems).
- Visual Basic for Applications. In this part of the module, students will learn how to take their Excel abilities to the next level by wrapping their spreadsheet models into friendly applications for the end users. Through guided demonstrations, students will develop a variety of applications, including financial, logistics and business management applications.
The module will be subject to continual refinement to ensure the content is kept relevant to industry's usage of spreadsheets.
The aim of the module is to give students hands-on experience in using industry-standard simulation modelling software in order to structure and solve complex and large-scale managerial decision problems.
The module will cover the following indicative topics.
• Queuing theory: Students will be introduced to the basic underpinnings of queuing theory, including key assumptions, benefits, and limitations.
• Discrete-event simulation: Core theory of discrete-event simulation will be covered, including a review of simulation mechanics, how to incorporate randomness into a simulation, and the systematic analysis of simulation model results. This will be supplemented with practical training in how to build and run simulation models using commercial software. Example applications will be drawn from a variety of sectors, such as manufacturing/production, transportation, healthcare, and other service industries (e.g. banking, retail, customer service).
The aim of this module is to enable students to apply basic statistical inference methods for tackling real-world business questions and equip them with basic knowledge of the R statistical programming package.
The module covers two indicative areas:
1. Business Statistics: Students will learn about descriptive analysis of quantitative data, focusing mainly on how to effectively summarise data, and inferential analysis of quantitative data, which includes identifying key properties of a given dataset, deriving point and interval estimates, hypothesis testing, correlation analysis, and simple linear regression.
2. Python programming package: This will cover the Python programming language and introduce students to basic and more advanced concepts within Python, as well as how to use Python for performing statistical data analyses.
The aim of this module is to introduce students to optimisation modelling and solution techniques, typical applications areas within strategic/operation business planning, and the use of commercial optimisation software.
The module covers the following indicative topics:
• Linear Programming: Students will be introduced to the building blocks of optimisation (i.e. decision variables, objectives, constraints), how to mathematically formulate linear programming (LP) models, LP solution techniques, sensitivity analysis (e.g. range of optimality reduced costs, dual prices), and typical applications like production planning, scheduling, and portfolio selection.
• Network Models: This topic includes a range of concepts and modelling techniques for formulating classic network models, including transportation and assignment, shortest path, maximum flow, and minimum spanning tree problems, and common solution approaches.
• Integer Programming: This will cover integer linear programming (ILP) models, including binary integer models, classic exact and heuristic solution methods (e.g. branch and bound, greedy heuristics), and typical application areas of ILP, including capital budgeting, fixed charge production, and facility location.
The module will develop students' understanding of corporate finance theory and its applications to the main problems faced by financial managers and corporate decision makers. The main topics that will be covered include corporate capital budgeting, investment decisions under uncertainty, cost of capital, sources of finance, capital structure, dividend policy and mergers and acquisitions (M&A) decisions.
This module will cover the following topics:
• Investment appraisal techniques and decisions
• Stock market efficiency – capital market behaviour
• Portfolio theory
• The Capital Asset Pricing Model
• Sources of finance
• Capital Structure
The aim of this module is to enable students to critically evaluate the roles warehouses, transportation centres and the different modes of transport have on the logistic and supply chain systems. It will also provide the student with an understanding of warehouse management activities, such as picking strategies and warehouse layout, packaging, etc and of distribution decisions, such as transport modes and single-, multi- or omni-channel planning. Students will be able to appreciate the use of appropriate methods that are used in practice and their impact in generating the company competitive advantage.
Indicative topics are as follows:
- Warehousing/Storage (the warehouse location, layout problem, storage equipment, picking strategies, packaging, labelling, etc)
- Inventory management (how much you need to stock to minimise your cost and retain your competitive advantage)
- Distribution & Global Transportation
* Global transportation and techniques adopted in practice (air, sea, railroads, trucks, motorbikes/bicycles, pipelines, others)
* Transport/road technology including software and hardware (trucking devices, software used, etc)
* Transport modelling and its impact on the environment and safety.
According to the traditional marketing concept, the Consumer is at the heart of all marketing activities. Thus, how consumers and organisations buy, own, consume and dispose of products, brands, marketplace communities, and experiences is the heart of marketing. Consumption is researched by a diverse array of disciplines including economics, anthropology, psychology, sociology and cultural studies, (human) geography, history and linguistics and political science. This interdisciplinarity has brought great depth and complexity to marketing's understanding of consumption.
Although the focus of this module is consumer behaviour, organisational behaviour will also be explored. Students will develop an understanding of how theories relating to consumer and organisation decision-making, and buyer behaviour inform marketing practice. There will be an emphasis on (i) a micro-level analysis, which relates to more immediate or individual aspects of Consumer and organisational buying behaviour; and (ii) the macro-level, relating to how the broader environment and cultural issues influence consumption.
In today's competitive and global economy, companies are turning to project management to consistently deliver business results. Increased number of international and complex projects brings with it a growing demand for project management specialists, according to Project Management Institute (PMI). This module introduces the principles and practice of project management in a global context. The module aims to:
Equip you with project management tools, techniques and management issues, focusing on key challenges that arise from managing complex projects, such as with regards to project time, quality and cost, resource constraints, stakeholder analysis, cultural diversity and teamwork.
Analyse contemporary project management issues and employ a range of established and innovative methodologies for adequate project plan, execution and control;
Critically analyse risks in projects, develop sustainable contingency plans and demonstrate ability to set reasonable and achievable deadlines and milestones across different project tasks with due consideration to economic, social, and environmental aspects surrounding a project.
The operations management function has always been of vital importance in a wide variety of organisations and industries whether manufacturing- or service-oriented, public or private, small or large. With the rise of Industry 4.0, managers are expected to continuously optimise operations to enable even faster, more flexible, and more efficient processes to create and deliver higher-quality goods and services at reduced costs. This digital revolution means that operations managers need to be prepared to face extraordinary levels of complexity and competitive pressures. Indicative topics include:
1. Provide with fundamental knowledge in operations management and understanding of how operations are being transformed by digital technologies, such as Blockchain, IoT, Big data, Cloud computing, driverless vehicles and 3D printing.
2. Inform and debate how operations management can deliver real competitive advantage by managing and leading digital transformation in businesses
3. Discuss the challenges of operations management to leverage the principles of Industry 4.0 to drive efficiency into the creation and delivery of products and services
This module will cover the design, planning, execution, control, and monitoring of supply chain activities, such as supplier relationship, production, inventory, transportation and demand management. Strategic questions regarding efficiency versus responsiveness will be addressed with the objective of creating net value, building competitive strategies, leveraging worldwide logistics and synchronizing supply with demand. The module will equip students with appropriate methods that are adopted in practice.
The module will be given in two parts with indicative topics to include:
- An overview of logistic systems and supply chain management, the various activities involved, the main supply chain drivers, responsiveness vs. efficiency, pull versus push strategies and global supply chain management strategies.
- Appropriate techniques to enhance the efficiency and responsiveness of supply chain activities, including the distribution design and planning (e.g., where to locate facilities and how to transport goods), the inventory control (to guarantee high customer service levels) and the forecasting activity (to plan operations capacity levels).
Stage 2 consists of one compulsory module, a dissertation. This is a detailed study using relevant business analytics techniques to evaluate a chosen company.
This module allows students to put into practice the knowledge and skills gained in the other modules on the MSc Business Analytics. Working under the guidance of an academic supervisor and possibly with a company, students solve practical problems that require an application-oriented thinking. The problems are varied and interesting, such as analysing marketing campaigns, ranking credit risks, optimising capital investments, forecasting sales trends, simulating patient flow through hospitals and extracting patterns from large datasets.
We use a variety of teaching methods, including:
Classroom-based learning is supported by the latest online technologies and learning platforms.
Your progress on this course is assessed by coursework only. Students wishing to undertake the optional industrial placement will be required to successfully complete all stage 1 modules. The Industrial Placement is assessed by the completion of the Industrial Placement Report.
The 2022/23 UK fees for this course are:
For details of when and how to pay fees and charges, please see our Student Finance Guide.
For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact email@example.com.
The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.
Find out more about general additional costs that you may pay when studying at Kent.
Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:
Kent Business School is a research-led business school. Our research strategy is developed around the core theme of sustainable innovation which cuts across the entire School. This theme can be seen as being divided into two sub-strands of research aimed at answering these main questions:
Kent Business School advances knowledge through constant promotion and support of innovative research. We have an impact on wider society through extensive collaborations with external partners which range from other academic institutions to a variety of local, national and international businesses as well as the NHS. Within this wider context, our main strategic aim has been geared towards establishing ourselves as a leading institution for research in sustainable innovation.
Kent Business School is a global leader in research and develops a wide portfolio of research related activities including workshops, conferences and research seminar series. This has led to a large number of international collaborations and to over 200 co-authored papers with international partners.
Specialising in public-sector critical accounting and accounting history.
Looking into a wide array of financial issues from derivatives pricing to real-estate modelling.
Innovating in wide-ranging topics such as operational research and systems thinking.
Studying issues surrounding consumer behaviours, product development and maintaining value supply chains among others.
Specialising in improving human resource management, organisational behaviour and leadership.
Helping in the development of innovative business strategies for business all over the world.
Helping companies to solve complex strategic, tactical and operational problems.
Contribute to the productivity debate and drive improvements at all levels; from the national economic output, to changes in the ways SME’s operate.
Providing quantitative analysis of issues in the financial markets for businesses and policy makers.
Helping both academics and practitioners tackle the challenges emerging from the rapid development of new digital technologies
Dynamic Publishing Culture
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Critical Perspectives on Accounting; Quantitative Finance; Human Resource Management Journal; Journal of Product Innovation Management; European Journal of Operational Research; and Psychology & Marketing
Full details of staff research interests can be found on the School's website.
This specialist programme prepares students for roles within business analytics.
Our Business Analytics graduates find work in public and private sectors, both overseas and in the UK, in a wide range of companies and organisations, including:
Many of our students also stay local and find job opportunities regionally in small and medium firms or even set-up their own businesses as well-equipped entrepreneurs.
You gain much more than an academic qualification when you graduate from Kent Business School – we enhance your student experience and accelerate your career prospects.
In today’s business climate employers are increasingly demanding more from new employees, we are therefore proud that they continually target our graduates for their organisations across the globe. Employers respect our robust teaching and reputation for delivering international business expertise, leading global research and an outstanding international learning experience.
From the moment you start with us, our efforts are focused on helping you gain the knowledge, skills and experience you need to thrive in an increasingly competitive workplace.
Kent Business School has an excellent international reputation and good links with businesses locally and globally. Our qualified careers practitioners provide support to all business postgraduate students for up to three years after graduation.
In addition, Careers and Employability Service at the University provide a comprehensive package of skills development training programmes, careers advice, volunteering and paid work opportunities to enhance your career prospects.
Kent Business School has a lively and active postgraduate community, brought about in part by our strong research culture and by the close interaction between our staff and students. Staff publish regularly and widely in journals, conference proceedings and books and embed their research in their teaching.
Taught students have regular contact with their course and module conveners with staff on hand to answer any questions and to provide helpful and constructive feedback on submitted work.
The Business School has an active and inclusive extra-curricular academic and social scene with guest lectures, talks and workshops organised by our academic staff, research centres and the ASPIRE team. You can catch up with our most recent Open for Business Seminar Series.
The award-winning Sibson Building is Kent Business School's home on our Canterbury campus. This vibrant, state-of-the-art structure includes lecture theatres, seminar rooms, dedicated MBA, PhD and IT suites as well as social and breakout areas to fully enhance your learning experience.
Kent’s libraries offer over a million books, periodicals and journals, and we have subject-specific librarians to help you secure access to the information you need.
Kent Business School has close links with: ifs (Institute of Financial Services); dunnhumby, who partners the Consumer Insight Service in the Centre for Value Chain Research; Hong Kong Baptist University, with whom we offer a joint Master’s programme in Operational Research and Finance Business Statistics; University of Castellanza (Italy); Audencia Nantes Business School (France); Aarhus School of Business and Social Sciences (Denmark); Universiti Teknologi Malaysia; University of Ingolstadt, Bayern (Germany); City University of Hong Kong; Renmin University of China, School of Business.
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.
Learn more about the applications process or begin your application by clicking on a link below.
Once started, you can save and return to your application at any time.