MSc Business Analytics 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:
- IBM Research
- 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.
MSc Business Analytics will reopen for one final application round on Monday 2 March 2020 to all students and will close to all applications on Tuesday 31 March 2020.
Applications may be closed earlier depending on how many places are still available.
Academic English preparation and support
If you require additional support to take your language skills to the required level, you may be able to attend a presessional course at the Centre for English Language Education, which is accredited by the British Council for the teaching of English in the UK. Students who successfully complete the presessional course to the required level can progress to postgraduate study without retaking IELTS or equivalent.
Specialist 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 course deposit. For more details, please contact us.
- 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 underpinned by the latest developments
- An inspiring research portfolio worth £799m
- 91.1% of MSc graduates from Nottingham University Business School secured work, self-employment or further study within six months of graduation
- More than 19,000 Business School alumni connect you to a powerful global network of business contacts
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 dissertation over the summer, and will be allocated an appropriate dissertation supervisor who will oversee your progress.
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.
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.
Consumer Behaviour and Analytics
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.
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
Supply Chain Planning and Management
The module takes a dual approach covering both the business processes and the quantitative models and techniques necessary for supply chain planning and management. It is divided into three major parts.
- Supply chain concepts and definitions:
- Fundamental planning and control concepts for supply chain and operations planning: classification of operational and supply systems
- Inventory - forms, functions, decisions, models
- Capacity – definitions and planning
- Forecasting for supply chain and production management:
- Planning, scheduling and control approaches: aggregate planning, hierarchical planning and control
- MRP-based planning and control
- JIT principles, kanban systems
- Theory of constraints (TOC)
- Enterprise Resource Planning (ERP) systems
- Supply chain collaboration:
- Planning and control across the supply chain
- The bullwhip effect
- Supply chain collaboration approaches – continuous replenishment
- Vendor-Managed Inventory (VMI)
- Collaborative Planning Forecasting and Replenishment (CPFR)
Analytics Specialisations and Applications
An in-depth look at specialised analytical techniques which present significant opportunities within business environments to extract actionable insights. Applications covered include Recommender Systems (for example, collaborative filtering in business), Text Analytics (linguistic processing, social media analysis), Spatial/Temporal analytics (for example, financial time series), Network analytics (for example, social graph analysis) and High dimensional analytics.
Leading Big Data Business Projects
This module explicitly focuses on technologies, planning and managerial issues associated with leading big data projects in business. Key concepts revolve around:
- using data analytics in context (integration of qualitative and quantitative approaches, introduction to survey methods and design)
- the full data lifecycle (including data management and security)
- introduction to organisational scale IT infrastructure
- project management
- presentation skills
Machine Learning and Predictive Analytics
This module builds on Foundational Business Analytics covering more advanced predictive models and their motivation within business use cases. Students will establish knowledge of state-of-the-art prediction techniques including SVMs, temporal 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. Focusing on the applicability of models to real world problems the module will consider the appropriateness and utility of each method with respect to common ''tricky'' data properties in real world data that lead to under-performing models.
Examples include unbalanced classes, heterogeneous input feature types and detrimentally large number of input features. Within the module methods to unpack the various predictive models to understand why they predict what they do and the utility of this information in various business contexts will be covered.
This module is taught primarily using Python against a background of industrial workflow data modelling environments (for example, SPSS Modeller, Orange) where applicable.
Advanced Operations Analysis
Module content is organised around four themes:
- 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)
- Shop floor control: WIP and Little’s law; introduction to operations scheduling and sequencing
- Introduction to distribution logistics modelling, reverse logistics and closed-loop supply chains
The module introduces you to marketing theory and practice. Particular attention will be given to 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.
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.
The above is a sample of the typical modules that we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. This course page may be updated over the duration of the course, as modules may change due to developments in the curriculum or in the research interests of staff.
Teaching methods and assessment
You will be assessed through a combination of individual assignments or group projects and written exams.
Career destinations for our postgraduates include:
- finance and investment analysts
- higher education teaching professionals
- investment bankers
- IT business analysts
- management consultants
- marketing professionals
- public relations professionals
- university researchers
Postgraduate careers team
Our in-house Postgraduate Careers Team provides expert advice and guidance so that you can make an informed decision about the right career path for you.
As soon as you have accepted your offer of a place at the Business School, we can begin working with you to support your career planning needs. You can take part in pre-course careers discussions and take advantage of remote and online support through Career Leader, an online assessment tool which helps you to measure your business interests and motivations before starting your course.
Our support continues throughout your time at Nottingham and after you graduate.
Average starting salary and career progression
91.1% of postgraduates from Nottingham University Business School secured work or further study within six months of graduation. £25,000 was the average starting salary, with the highest being £57,200.*
* Known destinations of full-time home postgraduates who were available for employment, 2016/17. Salaries are calculated based on the median of those in full-time paid employment within the UK.
Careers support and advice
We offer individual careers support for all postgraduate students whatever your course, mode of study or future career plans.
You can access our Careers and Employability Service during your studies and after you graduate. Expert staff will help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.
More than 1,500 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.
As a student on this course, you should factor some additional costs into your budget, alongside your tuition fees and living expenses.
You should be able to access most of the books you'll need through our libraries, though you may wish to purchase your own copies or more specific titles.
Scholarships and bursaries
See information on how to fund your masters, including our step-by-step guide. Further information is available on the school website.
Government loans for masters courses
Masters student loans of up to £10,906 are available for taught and research masters courses. Applicants must ordinarily live in the UK or EU.
International and EU students
Masters scholarships are available for international and EU students from a wide variety of countries and areas of study. You must already have an offer to study at Nottingham to apply. Please note closing dates to ensure you apply for your course with enough time.
We provide guidance on funding your degree, living costs and working while you study. You can also access specific funding opportunities, entry requirements and other resources for students from specific countries.