MSc Business Analytics
Providing you with in-demand skills for solving challenging business problems.
About The Course
We live in a world where analytical decision-making happens every second. Data is collected about everything in order to construct, operate and maintain systems. If you want a career in decision support, operational research, industrial engineering or management science, this is the ideal programme for you.
This course will train you in analytical decision-making. Not only do you learn the theory of business analytics but also how to apply it in practice. This involves generating relevant business insights using data-driven methodologies and tools. Our programme is one of the few to teach the entire Business Analytics life cycle, covering Descriptive, Predictive and Prescriptive analytics.
We have excellent partnerships with industry business analytics practitioners. We constantly update this programme to reflect the dynamically changing landscape of business analytics. We place a very high emphasis on creating graduates with skills that are valuable in the job market. For example, you will experience a real-life analytics project as part of your course.
12-month course, starts in October.
Designed for students interested in careers in operations research, business analysis, problem solving, data mining, strategic planning and supply chain management.
The MSc in Business Analytics consists of compulsory and optional modules, plus a project. The compulsory modules ensure that you have a firm grounding in important subjects. The wide range of optional modules allows you to specialise in subjects that particularly interest you.
During your first term from October to December, you will study four core modules:
Operational Research and Prescriptive Analytics
This module provides an introduction to Business Analytics and Operational Research. It begins with a description of the origins of the subjects, an overview of their subsequent development, and a discussion on how to model real-life problems adequately. The remainder of the course gives an overview of some of the most widely used models and solution methods, including decision analysis, linear programming, inventory control, simulation and Markov chains.
Statistics and Descriptive Analytics
At the heart of many management problems lies data that need to be described, analysed and interpreted. An operational researcher/management scientist needs to be able to do this soundly and efficiently. The overall objective of this module is to develop the ability to describe, analyse and interpret data soundly, making effective use of computer software. This module assumes some prior knowledge of statistics (although we know that some of you have plenty!) and some familiarity with simple algebra and calculus is assumed. This module emphasises the practical application of statistical methods, and makes extensive use of SPSS.
The second part of the course runs from January to May, and includes at least three from the following four modules, plus a choice of two or three optional modules on the next tab (totalling six modules).
Simulation and Stochastic Modelling
The aim of this module is to teach the skills required to apply simulation successfully to help improve the running of an organisation, whether in the public or private sectors, manufacturing or services.
Modern simulation packages are a valuable aid in building a simulation model and this module will employ a widely used and up-to-date discrete event simulation package. However, without the proper approach, the results of a simulation project can be incorrect or misleading. This module looks at each of the tasks required in a simulation project. It emphasises the practical application of simulation, with a good understanding of how a simulation model works being an essential part of this.
Optimisation and Heuristics
Optimisation, sometimes called mathematical programming, has applications in many fields, including operational research, computer science, statistics, finance, engineering and the physical sciences. Commercial optimisation software is now capable of solving many industrial-scale problems to proven optimality.
The module is designed to enable students to apply optimisation techniques to business problems. Building on the introduction to optimisation in the first term, students will be introduced to different problem formulations and algorithmic methods to guide decision making in business and other organisations.
You will also choose two or three optional modules from those listed below.
Introduction to Python Programming
Python is a simple, yet very powerful, high level computer programming language that becomes immensely popular in our days. It is widely used in many scientific areas for data exploration and at the same time it is the preferred programming language among a wide range of modern organisations.
This course is an introduction to computer programming using Python for students without any prior programming experience. It introduces the basic principles of computer programming but is doing it with an emphasis on examples from the areas of business analytics and finance.
Every managerial decision concerned with future actions is based upon a prediction of some aspects of the future. Therefore Forecasting plays an important role in enhancing managerial decision making.
After introducing the topic of forecasting in organisations, time series patterns and simple forecasting methods (naïve and moving averages) are explored. Then, the extrapolative forecasting methods of exponential smoothing and ARIMA models are considered. A detailed treatment of causal modelling follows, with a full evaluation of the estimated models. Forecasting applications in operations and marketing are then discussed. The module ends with an examination of judgmental forecasting and how forecasting can best be improved in an organisational context. Assessment is through a report aimed at extending and evaluating student learning in causal modelling and time series analysis.
Introduction to Intelligent Data Analysis (Data Mining)
This module develops modelling skills on synthetic and empirical data by showing simple statistical methods and introducing novel methods from artificial intelligence and machine learning.
The module will cover a wide range of data mining methods, including simple algorithms such as decision trees all the way to state of the art algorithms of artificial neural networks, support vector regression, k-nearest neighbour methods etc. We will consider both Data Mining methods for descriptive modelling, exploration & data reduction that aim to simplify and add insights to large, complex data sets, and Data Mining methods for predictive modelling that aim to classify and cluster individuals into distinct, disjoint segments with different patterns of behaviour.
The module will also include a series of workshops in which you will learn how to use the SAS Enterprise Miner software for data mining (a software skill much sought after in the job market) and how to use it on real datasets in a real world scenario.
Transportation and Logistics Analytics
The purpose of this module is to understand and use in somewhat simple contexts, some of the basic models from logistics.
Algebraic formulations will be used as vehicle for describing models and discussing their relationships. There will be a focus on modelling, the use of professional software, and the understanding of results. For problems where exact solutions are hard to achieve even for simple instances of the problem, heuristics will be discussed. The main topics which are covered are: facility location, network design, warehousing and inventory control, vehicle routing and scheduling, and environmental considerations in transportation and distribution operations.
Marketing Research Methods
Marketing research enables an organisation to better understand the market environment.
The main objective of conducting marketing research is to enable decision makers to make better decisions than if the latter were based only on intuition and guesses. At the heart of marketing research is information which facilitates the decision making process.
In this module we focus on the collection and use of information in marketing research but pay particular attention to the context of the problem. You will also have the opportunity to learn some transferable skills that relate to gathering and using information for business intelligence and decision making.
Operations and Supply Chain Excellence
Successfully managing its operations and its supply chain activities is central to any organisation’s ability to compete for revenues and resources.
The aim of this module is to introduce a series of innovations and capabilities in operations and supply chain management that have been associated with excellence and outstanding performance.
These include strategic procurement management, lean production principles, supply chain contract design and negotiation, supply chain financing and risk management, and managing business process flows.
The module will look at these subjects in both manufacturing and service contexts.
This module enables you to develop an appreciation of the dynamics of the international marketplace and the complex and challenging forces shaping this environment. It uses the principles and frameworks underpinning international marketing to assess how key marketing and consumer behaviour theories, models and concepts apply in an increasingly globalised and internationally competitive marketplace.
Our programme-specific scholarship for 2019 entry include the Academic Excellence, UK-EU and International scholarships aimed at high-achieving students with a strong academic or personal profile. We'll automatically consider you for these scholarships when you apply and if you are shortlisted we'll be in touch with the next steps, so it's best to apply as soon as possible. We also offer other scholarships - visit our Apply for Masters page to find out more.
The Robinson Scholarship is an award of £5,000 available only to applicants for the MSc Business Analytics. The award is for an outstanding applicant from a developing country, to contribute toward the cost of tuition fees. Applicants need to have an offer for the programme in order to be eligible to apply. Those wishing to apply need to complete the application form by 1st May 2019 and return it to the Programme Director, Dr Trivikram Dokka .
The Department of Management Science provides an extensive careers service and postgraduate students may expect to be eagerly sought after by employers. More than 40 major employers normally contact the Department each year to recruit. Many former students now hold senior positions in their organisation – as management scientists or as managers.
The Department has strong links with companies and organisations, many of which employ our alumni. Companies visit the department to make presentations and interview students as part of their selection process. In other instances, opportunities are advertised via the noticeboards and electronically on the student VLE. You are also asked to contact company recruitment offices directly.
Management Science, Operational Research, Logistics, Supply Chain and Market Analysis are seen by leading companies as the start of a fast track to promotion for high flyers with a numerate or scientific background. Experience has shown that if you have a postgraduate qualification, you will not only obtain a better starting job but will also receive more rapid promotion.
Organisations in which students have been offered jobs in the last three years or so include: