Business Analytics MSc

 
  

Fact file

Qualification
MSc Business Analytics
Duration
1 year full-time
Entry requirements
2:1 in any discipline; applicants should not have previously studied a significant amount of business analytics, but must have a 2:1 (or equivalent) in quantitative modules at degree level with a significant amount of mathematical/statistical content
Other requirements
Personal statement and a list of modules being studied in the final year (for applicants who have not yet completed their undergraduate degree) PLEASE NOTE: Eligible applicants will be placed on hold and considered alongside other applicants in January 2018. The highest performing proportion of applicants will receive offers for MSc Business Analytics.
IELTS
6.5 (no less than 6.0 in any element)

If these grades are not met, English preparatory courses are available
Start date
September
Campus
Jubilee Campus
School/department
Tuition fees
You can find fee information on our fees table.
 
This course is limited to 30 students and so early application is advised.

Overview

Do you want to learn how to turn data into business insights at a state-of-the-art teaching facility led by international experts? Are you interested in discovering cutting-edge analytics using real-world datasets, developing both your career and consultancy skills?
Read full overview

This course has been developed by the Neo-demographic Laboratory for Analytics in Business (N-LAB), a state-of-the-art teaching, data visualisation and research facility within the Business School. It is offered in collaboration with multinational business in order to provide the exact skillset that they are looking for.

As well as learning to harness big data tools, data science techniques and manage analytics projects, you will benefit from significant industry engagement.

N-LAB's partners span the world, and currently include:

  • Dunnhumby
  • IBM Research
  • Ipsos
  • NHS
  • Tesco
  • Tigo Mobile
  • Walgreens Boots Alliance
  • World Bank

In addition to guest lectures, coursework will be based on real-world datasets, providing hands-on practical experience in the techniques businesses are looking for, as well as required skills in managing practical business analytics projects.

Academic English preparation and support

Accredited by the British Council for the teaching of English in the UK, the University's Centre for English Language Education provides high-quality preparation and support. Our presessional courses take your English language and academic skills to the level you need to progress to postgraduate study without taking IELTS again.

Specialist five and 10-week business and management courses are available and you could be eligible for a joint offer, which means you will only need to apply for your visa once. Students who enter via the CELE route are exempt from paying the school's £2,000 reservation fee. For more details, please contact us.

Key facts

  • This course is delivered by N-LAB, which provides state-of-the-art research, data visualisation and teaching facilities
  • Part of an elite group of EQUIS and AMBA accredited business schools
  • 6th in the UK for research power in the latest Research Excellence Framework, with teaching informed by the latest developments
 

Course details

Across the autumn and spring semesters, you will take 120 credits of taught modules. Each module typically consists of 10 two to three hour sessions.

You will complete a 60-credit 12-15,000-word dissertation over the summer, and will be allocated an appropriate dissertation supervisor who will oversee your progress.

Assessment

You will be assessed through a combination of individual essays or group projects and written exams.

 
 

Modules

Core

Analytics Specialisations and Applications

Offering an in-depth look at specialised analytical techniques, this module highlights the significant opportunities they offer within business environments in extracting actionable insights. You will develop an understanding of how these advanced skills can bring competitive advantage in real-world business applications.

 
Data at Scale: Management, Processing and Visualisation

This module introduces the fundamental concepts and technologies that are used by modern international businesses to store, fuse, manipulate and visualise mass datasets. 

Key concepts include:

  • core database and cloud technologies
  • data acquisition and cleansing
  • how to manipulate mass datasets (focusing on SQL, Hadoop)
  • effective solutions to common data challenges (for example, missing data)
  • handling geospatial and open data
  • visualisation technologies (Tableau, PowerMap, QGIS, CartoDB)
  • web visualisation (HTML5)

All content is based around real-world business examples.

 
Data Driven Dissertation Project in Business Analytics

Representing the culmination of the programme, you will design, execute and report a research project based on the analysis of real-world or simulated data. This includes an 8,000-word dissertation, exhibits and data visualisations, and will need to satisfy scholarly objectives consistent with the execution of quality applied research in a business or social context.

 
Foundational Business Analytics

This module introduces fundamental statistical concepts and key descriptive modelling techniques in data science, while laying a foundation for the general programming skills required by any top modern business analyst (for example, Python/R).

A range of descriptive modelling concepts will be covered (such as feature engineering, clustering techniques, rule mining, topic modelling and dimensionality reduction) against a background of real world datasets (predominantly based on consumer data).

You will learn not only how to successfully implement foundational descriptive techniques, but also how to evaluate and communicate results in order to make them effective in actual business environments.

 
Leading Big Data Business Projects

This module explicitly focuses on technologies, planning and managerial issues associated with big data projects in business. Key concepts revolve around:

  • understanding requirements
  • coordination of a business analytics team
  • the data lifecycle
  • using noSQL solutions (for example, Hadoop, Pig, Hive, MongoDB)
  • linked data
  • taking solutions from evaluation to implementation (for example, A/B testing)
  • presenting persuasive results (for example, d3, advanced python and HTML5)
  • extending to real-time/stream business analytics
 
Machine Learning and Predictive Analytics

This module covers core predictive models and their motivation within business use cases. Introduces the key techniques that underpin this increasingly relevant field along with their evaluation (for example, measures of success, cross validation, A-B testing).

You will establish knowledge of state-of-the-art prediction techniques including classification models (for example, decision trees/forests, SVMs), Nearest Neighbour models, Bayesian methods, Ensembles and Deep Learning. Practical exercises will be set against a range of real world datasets and time series data.

This module is jointly taught using SPSS modeller and Python, giving you practical experience in industrial workflow data modelling environments where applicable.

 

One of:

Consumer Behaviour and Consumption

The module interrogates the concept of 'the consumer' and 'consumption'. It examines behaviour across the consumption cycle (through production, acquisition, use and disposal) addressing individual and contextual factors that shape behaviour at micro and macro levels.

It reviews the roots of research into consumer behaviour and consumption, covers particular theories and bodies of literature (for example, decision making, learning, habits, socio-cultural processes). It provides opportunities to apply theory to consumer behaviour and consumption in a variety of context and to assess the implications for commercial and non-profit organisations, public policy and consumers themselves.

 
Supply Chain Planning and Management

Module content is divided into three major parts:

  1. Fundamental supply chain concepts; The importance of supply chain management and logistics; Classification approaches; Buyer-supplier relationships and sourcing decisions.
  2. Supply chain management processes; Forecasting for supply chain and production management: qualitative and quantitative approaches (regression and causal modelling, time series methods); Inventory: forms, functions, decisions, and models. Inventory positioning. Supply chain dynamics and the bullwhip effect.
  3. Planning and control approaches, Aggregate planning. Hierarchical planning and control. MRP-based planning and control. Capacity management strategies. Enterprise Resource Planning (ERP) systems. Just-In-Time (JIT) and Theory of Constraints (TOC). Methods and techniques for planning and control.
 
Management Science for Decision Support

The emphasis in this module is on formulating (modelling) and solving models with spreadsheets. The topics covered include:

  • modelling principles
  • optimisation and linear programming
  • network models
  • introduction to integer programming
  • key concepts of probability and uncertainty
  • decision theory
  • queuing systems
  • simulation
 

Optional

Advanced Operations Analysis

This module covers:

  • more advanced forecasting techniques (including more advanced time series and causal models)
  • inventory modelling (quantity discount models; joint replenishment; reorder point , lot size systems; periodic review models; news vendor model; (S-1, S) model; multi-warehouse situations)
  • push/pull/conwip and TOC production systems
  • shop floor control; buffer management and line balancing
  • operations scheduling and sequencing
  • managing variety and variability; postponement; mass customisation
  • managing MRP based planning and control systems
  • organising the planning and control function, sales and operations planning and operations planning and control software
 
International Marketing

The module provides an overview of the changing international business environment and its challenges for international firms. It critically reviews contemporary issues in international marketing and provides insights into the development of competitive strategies and international marketing management within the context of consumer goods, industrial goods and services.

The module is designed to develop an appreciation of the special requirements for successfully conducting international marketing activities. The module aims to provide you with an in-depth understanding of current issues in international marketing theory and practice.

 
Quantitative Risk Management

The module covers:

  • the development of quantitative risk management and its use by firms to measure and manage their risk
  • measures of risk: value at risk, expected shortfall, and other risk measures
  • uses of quantitative risk measures: estimating risk measures - historical simulation approaches, parametric approaches and Monte Carlo simulation approaches
  • volatility forecasting
  • estimating liquidity risks
  • backtesting risk models
  • risk measurement using Extreme Value Theory
  • model and parameter risk
 
Supply Chain and Operations Strategy and Practice

Module content is divided into three major parts:

  1. Strategy, context of supply chain and operations strategy. The range of strategic decisions within and between operations. The impact of competition on operations and supply chains. Supply chain strategies for coordination and integration. Collaborative forecasting, planning and replenishment. Strategic perspectives of operations in the virtual and extended enterprises.
  2. Performance measurement, concept and importance of performance measurement within supply chain and operations management. Financial, non-financial, single and multi-factor measures. Approaches and techniques for developing customer facing and internal measures including Balanced Scorecard and Supply Chain Operations Reference (SCOR) model. Selection and application of key performance indicators. Importance of intra and inter-organisational benchmarking and approaches to target setting.
  3. Current practice, current supply chain management, logistics, and operations management approaches in specific industries/sectors. Pertinent issues and drivers of change in practicing supply chain and operations management.
 

 

The modules we offer are inspired by the research interests of our staff and as a result may change for reasons of, for example, research developments or legislation changes. This list is an example of typical modules we offer, not a definitive list.

 
 

Funding

Funding information is available on the school website and can also be found on the Graduate School website.

International and EU students

The University of Nottingham offers a range of masters scholarships for international and EU students from a wide variety of countries and areas of study.

Applicants must receive an offer of study before applying for our scholarships. Please note the closing dates of any scholarships you are interested in and make sure you submit your masters course application in good time so that you have the opportunity to apply for them.

The International Office also provides information and advice for international and EU students on financing your degree, living costs, external sources of funding and working during your studies.

Find out more on our scholarships, fees and finance webpages for international applicants.

 
 

Careers

Career destinations for our postgraduates include accountants, finance and investment analysts, higher education teaching professionals, investment bankers, IT business analysts, management consultants, marketing professionals, public relations professionals and university researchers.

Postgraduate careers team

Taught students benefit from the support of our postgraduate careers team who will help you to explore your career options and develop your career management skills. Our weekly MSc Advanced Career Leaders Programme is complemented by individual careers consultations, networking events and access to a wide range of employer presentations, volunteering activities and work experience opportunities.

Through a combination of your academic studies and the careers support on offer, you will be in an excellent position to enhance your career prospects and move onto the next stage of your career.

Employability and average starting salary

82.1% of postgraduates from Nottingham University Business School who were available for employment secured work or further study within six months of graduation. £28,500 was the average starting salary, with the highest being £50,000.*

* Known destinations of full-time home postgraduates 2015/16. Salaries are calculated based on the median of those in full-time paid employment within the UK.

Career and professional development

Whether you are looking to enhance your career prospects or develop your knowledge, a postgraduate degree from the University of Nottingham can help take you where you want to be.

Our award-winning Careers and Employability Service offers specialist support and guidance while you study and for life after you graduate. They will help you explore and plan your next career move, through regular events, employer-led skills sessions, placement opportunities and one-to-one discussions.

 
 
 
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Disclaimer
This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.

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