MSc Business Analytics

Gain an introduction to financial analytics by applying various techniques, including analytical, statistical, and mathematical, to financial market and investment portfolios. You will be introduced to various modelling and solving approaches to decision making problems arising in finance. 

You will look at the analytics process from data management, modelling, and computational tools perspectives, and review various widely used approaches to portfolio analytics, whilst being introduced to modelling approached for portfolio analytics system design.

You will also address the theoretical and practical aspects of various approaches, considering financial market data and the complexities of financial decision making problems. 

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.

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

This module provides an introduction to Supply Chain Analytics (SCA). It focuses on both the structural and operational elements of supply chain management: the design of supply networks as well as scheduling, inventory control, quality control and vehicle routing.

You'll become aware of the complexities and special issues related to supply chains and provide a basic understanding how these can be tackled.

SCA 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.  

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.

This 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 

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

Your final dissertation option 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 (internal applied research):

• 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

Previous dissertation titles (external consultancy project):

• Improving efficiency through supply chain data analysis (DHL)
• Advanced analytics to help a consumer save money (IBM UK Ltd)
• Understanding the time and price sensitivity of B2C delivery (Dixons Carphone Ltd)

The Business in Practice module is the core capstone module for students who choose this route instead of the dissertation route. It will illustrate business theory in practice by combining academic lecture input with expert practitioner insights, and will also provide intensive personal work-skills development via the WBS CareersPlus team. The module is taught over two intensive weeks incorporating an innovative and exciting business simulation.