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The final project is the most important part of the MSc Business Analytics program. It is a chance for you to independently conduct a large project on a business problem or issue of your choice or provided by a real organisation, with real datasets, using the analytics techniques covered in the program.The final project requires you to:- Choose a topic and get it approved by your supervisor.- Design and conduct a research plan.- Find and use relevant information sources.- Plan and manage your time effectively.- Communicate with your supervisor regularly.- Write a well-presented report.The final project is a test of your ability to use your analytics skills to solve a real-world problem. You will be assigned a supervisor to advise you, but it is your responsibility to manage and complete the project. It is a challenging but rewarding experience. It is your chance to apply everything you have learned in the program and to demonstrate your readiness for a career in business analytics.To be successful in the final project, you need to be able to:- Think critically and creatively to select and develop the right analytical model for the problem.- Work independently and manage your time effectively.- Handle and analyze large datasets.- Be comfortable with the uncertainty and complexity of such projects.

This module has a focus on change management and people analytics and importantly contributes towards a greater understanding of how to manage change and the key levers which support the successful implementation of change projects. People analytics plays an important part in this and this module explores how to develop people measures to diagnose potential areas of concern and to measure and track progress of change projects to inform current and future organisational strategy. The ability to manage change is a key HRM skill and often it is people professionals who lead and support both the diagnosis and implementation of organisational change projects. This module is focussed upon helping you to understand the complex nature of change, the different strategies that can be employed to manage it, the issues that people management professionals involved in the implementation of organisational change can face, and the key levers and mechanisms that can be used to both implement change successfully and to maintain change over the longer term. The module begins with consideration of the nature of the different types of organisational change which take place and the change models available to support both the diagnosis and management of change. It then goes on to consider how to identify and manage resistance both before and during change, as well as an examination of the key levers and mechanisms that can be utilised to help overcome resistance and sustain change over the longer term. Communication and participation are then studied in the context of leading change and overcoming resistance with a focus on how HRM professionals can involve people in the implementation of change and facilitate buy-in to different change outcomes.Reflecting on how culture change is altered over the longer term is a core aspect of sustainable change programmes and the theory is presented and discussed. Finally, the latter half of the module has a focus on people analytics and how measures can be developed to diagnose strategic activity and manage change, it also looks at how the presentation of data through a scorecard approach can be utilised to inform and measure the pace of change over the short and long term as well as informing both current and future strategic direction.

The module aims at introducing you to the new possibilities opened up by the digital revolution and how these can be translated into the field of global logistics. You will be exposed to several data analytic techniques, including data cleaning, data visualisation, and dashboard report development (in R) with a focus on application to global logistics and sustainability. More specifically the module will cover aspects such as:(i) Introduction to Data Analytics: understanding the big data landscape; (ii) Data Processing; (iii) Data Visualisation: telling a story; (iv) Analytical Techniques: Introduction to Descriptive, Predictive, Prescriptive and Cognitive; (v) Simulation/Network Analysis; (vi) Practical Issues: Dashboard Development

This module aims at introducing you to the new possibilities opened up by the business analytics revolution and how these can be used in the field of decision-making in business and management. You will be able to understand how different analytical techniques can be used to make the best business decisions. You will be exposed to several decision-making fields with business analytics, including management decision-making, types of managerial decision-makers, analytics in management decision-making, organizational readiness for data-driven decision-making, and decision-making with different analytical techniques. You will be able to identify the right analytical approaches for different business situations and make the best decisions. You will obtain practical managerial and analytical skills using R to make business decisions for organizations in different sectors.

In this module, you will develop in-depth understanding of the theory, practice and managerial implications of using digital analytics as part of an organisation's marketing strategy. The syllabus will introduce you to key principles and challenges, including the analysis and evaluation of data from social media, websites and search marketing to improve marketing performance. You will engage with a range of literature to reflect critically on contemporary issues and evaluate the role of big data ethics in an organisational context. In addition, you will get hands-on experience in key digital analytics tools used by marketing practitioners, resulting in strong strategic and applied knowledge in digital analytics upon successful completion of the module.

This module aims to provide you with a sound understanding of the approaches and techniques to structure, design and execute with rigour your final project of the program involving business issues informed by the experience of real organisations. In the first trimester, the module introduces you to a range of key generic, qualitative and quantitative techniques that are relevant to addressing your final project. In the second trimester, you will get the chance to take a deeper dive into the techniques that most suit your final project through workshops, computer labs and clinics.

Artificial intelligence (AI), machine learning, and ethics will be crucial to changing business models and decision-making in the future. AI is changing businesses and the way they work. Businesses are facing new technological solutions connected with big data and advanced analytics. This module aims to introduce you to how we can use AI in different businesses connected with analytics. You will be exposed to different areas of AI and analytics, like business intelligence, concepts, drivers, and major technologies of AI, including machine learning techniques, deep learning, robotics, the internet of things, etc. You will learn about the different types and methods of machine learning and how businesses have applied machine learning successfully. In addition, you will be able to understand the role of risk and ethics within AI, and how AI, machine learning and ethics have an impact on the performance of organizations. You will understand the different types of models, what kind of business questions they help answer, or what kind of opportunities they can uncover. By the end of this module, you will have a foundational understanding of AI in business and be able to apply these technological solutions to your business environment.

Have you ever wondered how streaming companies know what movies and TV shows you will like? Or how do retailers know which products you will want to buy? It's all thanks to Predictive Analytics. Predictive Analytics is a way of using data to predict future events. Businesses and organizations of all types use Predictive Analytics to make better decisions. Here's a simple example:Imagine you're running a lemonade stand. You want to know how much lemonade to make on a given day. You could just guess, but wouldn't it be better to know with more confidence how many people will want lemonade? You could use predictive modelling to figure this out. You could use data like past sales numbers, the day of the week, and the weather forecast to predict how many people will want lemonade on a given day.Predictive Analytics can be used to predict all sorts of things, like:- How many people will attend a concert?- How many products a company will sell?- How much traffic there will be on a given road?- How likely a customer is to churn?- How likely a student is to succeed at university? etc.In this module, you will learn about different predictive analytics techniques and how to use them to help your organisation make more accurate decisions about future events.

Decision-Making for OrganizationsOrganizations face many complex decisions every day. They need to find the best solutions to these problems in order to run their operations and plan for the future efficiently and effectively. This module will teach you how to use prescriptive analytics techniques to formulate and solve decision problems optimally.Part 1: OptimizationOptimization techniques use models to find the best solutions to problems with multiple variables and constraints. These techniques can be used to solve a wide range of problems in business, such as resource planning, investment planning, machine scheduling, logistics, and supply chain management.Part 2: SimulationSimulation is a technique that uses computer models to represent and analyse real-world systems. Simulation can be used to study a wide range of systems, including operational systems (such as hospitals, airports, and supermarkets) and strategic systems (such as the healthcare system and the supply chain).This module will give you the skills and knowledge you need to use prescriptive analytics to make better decisions in your organization.

Module is designed to ensure you are equipped with a longitudinal induction which ensures ‘How to be here’ foundation moves through Professionalism in classroom and beyond to Careers awareness and guidance as part of pass/fail attended module. This ‘levelling-up’ will provide an you with an enhanced experience if you have an identified skills gaps, and provide more skills balances for you within individual cohorts.