Business Analytics

This programme benefits from Surrey Business School’s excellent industry connections, equipping you with the expertise to analyse data and create the knowledge that leads to competitive advantages for business decisions.

Why Surrey?

At Surrey Business School, we take pride in the quality of our research and teaching. Our excellent standards are reflected in the findings of the last Research Assessment Exercise, our accreditations from the AACSB and the AMBA, and our close links with national and international businesses of all sizes and across all sectors.

Programme overview

Business analytics skills are more vital than ever in large organisations. They play a crucial role in supply chain management, operations management and finance, as businesses strive to increase their efficiency and productivity in order to build a competitive advantage.

This programme equips you with these skills, giving you the ability to interpret, conceptualise and convert Big Data into useful information that improves organisations’ performance. These skills are more vital than ever in large organisations and, as such, employees with an understanding of business analytics are increasingly in-demand in the job market.

The programme centres on two main areas: the ability to analyse business data, and the skill to solve business challenges analytically. Through your elective choices you can further specialise in either the economic or managerial aspects of the programme. Business analytics students often pursue careers as consultants, researchers, managers, and analysts.

Module descriptions

Data Analytics

This module is the science of examining raw data in order to support businesses and organisations in their decision making. This module looks at the relationships of entities in databases using the Structured Query Language to extract relevant information efficiently and uses statistical techniques to extract the essential management information. It also introduces unstructured data concepts. Special focus is given to Big Data, providing the knowledge, analysis and practical skills to gain additional business and customer insights.

Principles of Accounting

This module is designed to provide a practical study of the basic principles and advanced knowledge of financial accounting systems used around the world, and addresses the major issues to be reformed.

Supply Chain and Logistics Management

This module focuses on the supply chain management initiatives of large-scale retail and international businesses. Successful supply chain management is critical at both at an operational level and increasingly at a strategic level. An effective logistics infrastructure is essential to meeting customer expectations while minimising service costs.

Econometrics

This module builds on the statistical and econometric foundations, exploring a number of techniques for subsequent applied work, specifically concerning the estimation and inference of econometric models.

Preliminary Quantitative Methods

This module aims to familiarise students with conceptual and appropriate basic mathematical and statistical tools in economics, introducing simple linear regression techniques. This module has 20 hours of lectures, which are scheduled to take place in Week One.

Supply Chain Analytics

Management Science is used to solve supply chain aspects analytically. Techniques examine the Supply Chain’s underlying transportation network which connects suppliers via transshipment nodes to its demand locations.

Informatics for Management Decision Making

This module introduces the foundations of knowledge management, epistemology and semantics as sources to identify, capture, create, and distribute organisational knowledge. The module describes these strategies, along with the new roles and responsibilities for knowledge workers in the age of Big Data.

Managing Decision Implementation

This module looks at the diverse models and frameworks used to evaluate and implement organisational change. The module seeks to identify the means and mechanisms that promote organisational flexibility and agility.

Applied Marketing Research

This module provides knowledge about the critical aspects of applied marketing research theory and practice to support and improve marketing decision making. Market research proposal and its planning aspects are discussed. Techniques of applied marketing research and typical approaches are also examined.

Econometrics II

This module builds on the Econometrics I module. Asymptotically valid methods of estimation and hypothesis testing are introduced and we look at models involving several equations. Limited dependent variable and panel data models are also examined. Matrix algebra is used extensively to explore the properties of the models.

Economic Forecasting

This module is an introduction to economic forecasting. The module covers the following topics: forecasting trends, ARMA models of the cycle, modelling seasonality, forecasting with macroeconomic models, assessing forecasts and smoothing methods.

Business Process Management

This module examines the Big Data phenomenon. The module underscores the relationship between operations management on a day-to-day basis and its subsequent usage in modelling and analytics-driven managerial decision making. This module also provides hands-on experience with an enterprise software system (SAP).

Applied MSc dissertation

The MSc Programme will require you to undertake an applied MSc thesis*. The module is designed to allow you to undertake the development of a modelling-based decision tool. Students will be required to:

Identify and evaluate relevant measures and variables, as a source of decision-making insight.

Combine identified data or variables in a model that can be used as a tool for manager’s decision-making.

Use available data with a developed model to identify viable solutions and propose options and scenarios for organisational change and innovation that improves organisational performance.

Analyse a business relevant issue and develop recommendations and logical conclusions.

This is a great opportunity to do add real value to a business, company or industry.

*In the exceptional case that the student cannot do an applied thesis, a conventional MSc thesis may be approved by the programme director.

Software

You will get hands-on experience using a wide range of tools in the course. An indicative list of the software tools include:

• Apache Hadoop (Map Reduce) with Amazon’s Elastic Cloud or IBM’s Smart Cloud for distributed Big Data analytics
• SAP for Enterprise Resource Planning
• COGNOS and SQL Server for Business Inteligence and OLAP
• Excel (using the Solver and Data Analysis Add-Ins) for decision making
• SPSS and EViews for statistics and forecasting
• ILOG’s Optimisation Studio (Cplex) for supply chain analytics
• Matlab / Simulink (SimEvents) for simulations

Applicants should normally hold a Bachelors degree (UK 2.1 or above) or equivalent qualification from a recognised British or overseas university in a related subject (including accountancy, business administration, economics, engineering, finance, management, mathematics, physics or science).If an applicant’s Bachelors degree is not in a subject related to the MSc, some relevant work experience would be an advantage. Higher level professional qualifications may also be accepted. Each applicant is assessed on their own merit.English language requirementsIELTS minimum overall: 6.5IELTS minimum by component: 6.0 English Language Requirements IELTS band: 6.5 IMPORTANT NOTE: Since April 2014 the ETS tests (including TOEFL and TOEIC) are no longer accepted for Tier 4 visa applications to the United Kingdom. The university might still accept these tests to admit you to the university, but if you require a Tier 4 visa to enter the UK and begin your degree programme, these tests will not be sufficient to obtain your Visa. The IELTS test is most widely accepted by universities and is also accepted for Tier 4 visas to the UK- learn more.