MSc Business Analytics

Course Details

You will study four compulsory modules in term 1 to give you an overview of key business areas (plus the compulsory Project Skills module), and take four optional modules of your choice on this one-year course. Please note that availability and delivery modes may vary. All students will undertake a dissertation.

Assessment
Assessment is usually a mix of exams, group projects and coursework. Your dissertation brings all your learning together.

Programming skills
We support the learning of multiple programming languages with access to a variety of interactive online materials, covering R and Python (provided by Data Camp). Several modules feature application of such programming languages in their syllabus.

Dissertation
Your final dissertation is a 10,000 word piece of work, demonstrating that you can undertake systematic and rigorous applied research. Most students undertake individual academic research on a topic critical to effective decision-making in organisations, under the guidance and supervision of our academics. Some students are able to work in conjunction with an external corporate client to undertake applied research of interest to their organisation; these students will often complete a client report in addition to their dissertation. 

Previous dissertation titles

  • Effect Of Development Of Personalised Offers To A Sub-Segment Of Clients Of Unicredit Bulbank
  • Sainsbury's: An Application Of Multinomial Logit Modelling In E-Fulfilment Demand Management
  • Barclays: Optimising Branch Staffing Levels 
  • Improving Short And Long Term Sales Forecasting Methodology For A Mainly Project-Based Business 
  • Tackling Resource Contentions In Project Management
  • Exploiting Airbnb Data To Enhance Hotel Revenue Management
  • Demand Modelling For Bike Sharing
  • Travelling Salesman Problem: Investigating Special Structures In Optimisation

Laptop requirement
It is likely that some of the modules on the course will utilise Virtual Machines (VMs) to run certain software. As such, students undertaking the course are required to have their own laptop, running either Windows or Mac operating systems, with at least 8GB of RAM and at least 256GB SSD storage (Windows)/ 256GB storage (Mac). Laptops with less RAM may be used though the VMs will not run as efficiently. The latest specification guidance is available here.

 

Compulsory Modules

Data Management

The main aims of the module are to familiarise you with spreadsheets, relational databases, SQL and tools designed to work with big data. By the end of the module, you will be able to demonstrate:

  • an ability to work with spreadsheets
  • an ability to extract, manipulate, join and store data in databases
  • an ability to read and write SQL queries
  • basic conceptual understanding and ability to work with big data technologies.
Project Skills

This module conveys the skills necessary to conduct the dissertation project. This will encompass soft consultancy skills to define and conduct a project for a client, problem structuring techniques, project management, academic writing and legally compliant data handling.

Analytics in Practice

With this module you will become familiar with the cross-industry standard process for data mining. The aim of the module is to teach you how to structure and conduct an analytical project including visualisation and communicating the project's results to the end-user.

Business Statistics

Gain a foundation in the analysis and presentation of quantitative data. Examine the basic elements of probability and statistics, essential to management science and operational research, and undertake computer-based analysis using a statistics package.

Optimisation Models

The module aims to develop your interest in, and knowledge and understanding of, various optimisation models to support decision-making in organisations. You will learn about the theoretical underpinnings of these models as well as how they are used in applications. You will gain practical experience in modelling and problem-solving. Topics covered include:

  • Optimisation modelling: mathematical programming, including extensive studies of linear programming and dynamic programming
  • integer programming, introduction to non-linear optimisation, introduction to algorithms and heuristic.

The techniques mentioned are illustrated on a range of real-life applications. IT tools (Excel Solver, Python libraries, etc.) are used to demonstrate the usage of the theory in practice.

 

Example Optional Modules

Advanced Analytics: Models and Application

This module introduces advanced analytics using different optimisation models and demonstrates them with applications ranging from healthcare, sports, social networks, to asset management and fraud detection.

 

Forecasting

This module provides an introduction to current quantitative forecasting methods, and its overall aim is to develop practical competence in their use. The module concentrates on models for short term forecasting, as these illustrate all the basic principles of analysing, comparing and extrapolating different models.

Strategy Analytics

Develop skills to successfully help companies to develop and rehearse strategies using modelling and analytical techniques that support a strategic planning process.

 

Advanced Data Analysis

Explore a range of sophisticated statistical methods to convert information into knowledge. Gain practical experience in the use of specialised software to analyse large sets of data information, and be able to report on the analysis in a practical way for improved management decision-making.

Pricing Analytics

The module will provide the conceptual understanding, practical skills and experience in using programming tools for you to model and analyse demand, and to use the outcomes to optimise pricing or product availability decisions in an automated fashion. Pricing Analytics focuses on how a company should set and update pricing and product availability decisions across its various selling channels in order to maximise its profitability in an automated fashion. In other words, we are concerned with algorithms making real-time pricing decisions, rather than strategic pricing.

The emphasis is on teaching advanced statistical and optimisation concepts and techniques that are highly relevant in practice. These concepts and techniques are taught in R with the aim of enabling you to be able to develop pricing solution prototypes for real-world problems.

Discrete Event Simulation

Students will learn the theoretical underpinnings of discrete-event simulation and gain practical experience in problem solving using commercial simulation software.

Supply Chain Analytics

Supply Chain Analytics aims to introduce various (analytical, mathematical and statistical) techniques to analyse supply chain performance and to identify inefficiencies and risk factors in operational, managerial and financial aspects of a supply chain.

Text Analytics

The module offers an introduction to text analytics and the analytics of unstructured data. It has a strong employability aspect and uses R and the associated packages for practical applications of text mining. It covers the following topics:  

  • Text preprocessing and information extraction.
  • Advanced data normalization and data cleaning in databases. Visualization of text data.  
  • Part of Speech Tagging and Natural Language Processing techniques for text filtering and dimensionality reduction.
  • Sentiment Analysis and Opinion mining with applications to social media data
  • Predictive modeling and forecasting using text data. 
  • Applications of Text Mining

Dissertation

Dissertation

Your final dissertation is a 10,000 word piece of work, demonstrating that you can undertake systematic and rigorous applied research. Most students undertake individual academic research on a topic critical to effective decision-making in organisations, under the guidance and supervision of our academics. Some students are able to work in conjunction with an external corporate client to undertake applied research of interest to their organisation; these students will often complete a client report in addition to their dissertation. 

 

See indicative compulsory and optional modules for this course More Less

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