Triangle

Course overview

Our Business Analytics MSc is taught in collaboration with multinational companies and will give you the essential skillset they are looking for. It 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.

You will benefit from the engagement of N/LAB's multi-national partners through their support for teaching and access to data.

You have the option to take industry-recognised digital qualifications by Microsoft and SAP alongside your course, which will develop your digital skills.

Our course will help you to become a business-orientated data scientist with a technical skillset, the ability to harness big data tools and the managerial skills to deliver practical business analytics projects. It will prepare you for senior management positions within the broad scope of the digital economy.

Why choose this course?

Delivered by N-LAB

which provides state-of-the-art research, data visualisation and teaching facilities

Gain digital skills

We offer the opportunity to take industry-recognised Microsoft and SAP certifications at significant discounts from the open market rate

Triple accredited

Part of an elite group of business schools worldwide to gain ‘triple crown’ accreditation

EQUIS, AMBA and AACSB accredited

More than 19,000

Business School alumni connect you to a powerful global network of business contacts

Course content

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.

Modules

Semester one

Core modules

Data Management and Manipulation

This module covers the following:

  • Introduction to information systems in organisations including hardware, software, telecommunications, types of information system and systems development
  • Relational database design
  • SQL as a data definition language
  • SQL as a data manipulation language
  • Data manipulation in a language such as R
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.

Optional modules

One from:

Entrepreneurship in Context

This module covers:

  • definitions of entrepreneurship/entrepreneurial activity
  • the theoretical perspectives underpinning the study of entrepreneurship
  • understanding what shapes the practice of entrepreneurship both in different settings (for example, social entrepreneurship, technology, family business, international entrepreneurship, environmental business, social media) and due to contextual influences (for example, influence of gender, policy)
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
Supply Chain Planning and Management 20 credits

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.

  1. 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
  2. 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
  3. 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)

Semester two

Core modules

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
  • ethics
  • 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.

Optional modules

One from:

Advanced Operations Analysis

Module content is organised around four themes:

  1. More ‘advanced’ forecasting techniques (including more advanced time series and causal models)
  2. 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)
  3. Shop floor control: WIP and Little’s law; introduction to operations scheduling and sequencing
  4. Introduction to distribution logistics modelling, reverse logistics and closed-loop supply chains
Digital Marketing

Lecture topics may include digital marketing definition and concept, digital marketing media, digital marketing communication strategy, digital advertising, social media marketing, email marketing, mobile marketing, content marketing, e-commerce vs digital vs internet marketing.

Summer

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 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. Modules (including methods of assessment) may change or be updated, or modules may be cancelled, over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for information on available modules. This content was last updated on Thursday 21 July 2022.

Learning and assessment

How you will learn

  • Lectures
  • Seminars
  • Tutorials
  • Workshops

Digital professional skills certifications

We offer the opportunity for you to take industry-recognised Microsoft and SAP certifications alongside your degree programme at significant discounts from the open market rate. This will enhance your digital capability, differentiate your CV and help you stand out to future employers. Find out more on our digital professional skills website.

How you will be assessed

  • Dissertation
  • Examinations
  • Essay

Modules are assessed by a combination of exams and coursework at the end of the relevant semester.

Contact time and study hours

10-credit taught modules will consist of 100 student learning hours, of which around 22 hours are associated with lectures and seminars. The rest of the time will consist of assessment preparation, class preparation, and private study.

20-credit taught modules will consist of double this time.

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2023 entry.

Undergraduate degree2:1 (or international equivalent) in any discipline; applicants should not have previously studied a significant amount of business analytics, but must have a 2:1 (or international equivalent) in quantitative modules at degree level with a significant amount of mathematical/statistical content

Applying

You are required to submit a personal statement and a list of modules being studied in the final year (for applicants who have not yet completed their undergraduate degree).

Spaces on this course are limited and, as such, applications will open in the following windows:

  • 22 July 2022 to 26 September 2022
  • 24 October 2022 to 30 November 2022
  • 6 February 2023 to 6 March 2023

The course will close to all applicants after each window. Applications will then be considered against each other and offers made to the top performing proportion of applicants in each round of selection. Please allow four weeks from the closing date of each window to receive a final decision.

Please note that this is a highly competitive course and there are a limited number of places available. The school reserve the right to close this course to applications when capacity is reached, and early applications are encouraged.

Our step-by-step guide covers everything you need to know about applying.

How to apply

Fees

UK fees are set in line with the national UKRI maximum fee limit. We expect fees for 2023 entry to be confirmed in August 2022.

Additional information for international students

If you are a student from the EU, EEA or Switzerland, you may be asked to complete a fee status questionnaire and your answers will be assessed using guidance issued by the UK Council for International Student Affairs (UKCISA) .

These fees are for full-time study. If you are studying part-time, you will be charged a proportion of this fee each year (subject to inflation).

Additional costs

All students will need at least one device to approve security access requests via Multi-Factor Authentication (MFA). We also recommend students have a suitable laptop to work both on and off-campus. For more information, please check the equipment advice.

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.

Funding

Business School MSc scholarships

There are many ways to fund your postgraduate course, from scholarships to government loans.

We also offer a range of international masters scholarships for high-achieving international scholars who can put their Nottingham degree to great use in their careers.

Check our guide to find out more about funding your postgraduate degree.

Postgraduate funding

Careers

We offer individual careers support for all postgraduate students.

Expert staff can help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.

Each year 1,100 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.

International students who complete an eligible degree programme in the UK on a student visa can apply to stay and work in the UK after their course under the Graduate immigration route. Eligible courses at the University of Nottingham include bachelors, masters and research degrees, and PGCE courses.

Graduate destinations

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.

Prior to commencing your course you can take part in pre-entry careers discussions and once on programme our MSc Accelerated Career Leader Programme is complemented by one to one career coaching.

Increasingly, graduates are required to be cloud and data-ready for the workplace with 66% of employers wanting to see graduates achieve professional qualifications as well as their main degree (CMI 21st Century leaders report). The school works with some of the world’s leading business software providers including SAP and Microsoft, offering the option to take their globally recognised professional digital qualifications alongside your course. Our Digital Centre of Excellence will support you so that you can develop the digital skills necessary to pursue your chosen career and stand out to future employers.

Our support continues throughout your time at Nottingham and after you graduate. Business School postgraduates also have access to events and resources provided by the Careers and Employability Service.

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
  • university researchers

Some MSc graduates have gone on to doctoral studies, others have become entrepreneurs. Our Ingenuity Lab has supported a number of our MSc graduates in starting their own company.

Career progression

86.2% of all postgraduates from Nottingham University Business School secured graduate level employment or further study within 15 months of graduation. The average annual salary for these graduates was £36,668.*

* HESA Graduate Outcomes 2019/20 data published in 2022. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

Two masters graduates proudly holding their certificates

Related courses

This content was last updated on Thursday 21 July 2022. Every effort has been made to ensure that this information is accurate, but changes are likely to occur given the interval between the date of publishing and course start date. It is therefore very important to check this website for any updates before you apply.