Business Analytics MSc



Equip yourself with the knowledge, skills, and experience needed to become a business-ready analytics professional

Overview

Our MSc Business Analytics program equips you with the knowledge, skills, and hands-on experience you need to become a business-ready analytics professional.

This course is hands-on and focuses on the practical application of analytical techniques in business settings, rather than their mathematical underpinnings. The course is a good fit if you aspire to a new career in business intelligence, business insight, business analysis, management consultancy or simply wish to make better use of data and more accurate decisions in your current field.

The curriculum aligns with the Certified Analytics Professional (CAP) qualification, potentially shortening your path to CAP certification.

a close-up of a hand holding a pen pointing at an iPad with data on it

Mode of Study:

Full-time

Duration:

1 years

Start date:

Sep

Course details

In today's data-driven world, businesses are eagerly looking for individuals with the expertise to extract meaningful insights from the volumes of data now available to them. Our MSc Business Analytics program equips you with the knowledge, skills, and hands-on experience you need to become a business-ready analytics professional.

You'll gain the knowledge and practical experience to effectively utilise descriptive, prescriptive, and predictive analytics to make sound business decisions and drive success within any organisation.

A key design thread linking the program's modules is the development of performative competency. Together, the modules you study will develop your ability as a  'business-ready' analytics professional who can choose the best techniques to address different business problems, formulate models with software and programming tools, and interpret and then persuasively communicate findings to both a technical or lay audience.

Compulsory Modules


Analytics Final Project

Data Analytics

Decision-making with analytics

Final project Development

Machine Learning, AI and Ethics

Predictive Analytics

Prescriptive Analytics

Optional Module

Business Analytics and Change OR Digital Analytics Strategy

 

  • calendar

    How you’ll be taught

    The course will utilise a range of teaching and learning methods to ensure that students achieve the learning outcomes.

    Learning activities will include:


    - Lectures, tutorials and seminars;

    - Individual Modelling Assignments;

    - Computer Labs;

    - Class debates and discussions;

    - Private Study;

    - Internet and digital research;

    - Problem-based learning involving ‘real world’ organisations; and

    - Simulations.

    Class activities and problem-solving exercises will enable you to gain feedback about your knowledge and understanding, before any formal summative assessments. 

  • note and pen

    Assessments

    A range of assessment methods are used in this program to enable you to demonstrate your achievement of the intended learning outcomes, including: - Individual computer modelling tasks where you submit a model;


    - Individual written assessments, including layperson, executive summaries, technical analysis reports and model documentation;

    - Poster displays and presentations;

    - Capstone projects involving ‘real world’ organisations;

    - Business simulations;

    - Reflective reports.

    To enable you to customise your program to your learning styles and interests, both the learning methods and assessments will allow you as much flexibility as is feasible. For example, you may choose the topic, materials, databases, analytic techniques, group members, etc. for an assignment. Similarly, teaching and learning topics will be related to the latest business practices from diverse industries, allowing you the chance to learn from the examples most suit your interests.

    We recognise that not all students may undertake learning and assessment as specified. Therefore, to ensure that the course is inclusive of and considerate of diverse needs, we will make alternative, individualised, arrangements if you are not able to complete learning and teaching sessions or assessments in the specified manner.

  • briefcase

    Work placement

    There is no work placement on this course but learning activities will involve working with real organisations to enable you to see how business analytics operates in a commercial context, while providing the opportunity to practice workplace-relevant skills.
  • library

    Facilities

    You will study at our Craiglockhart campus

Modules

Modules that you will study* as part of this course

Analytics Final Project ( SOE11170 )

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.

Further information

Business Analytics and Change ( HRM11127 )

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.

Further information

Data Analytics ( SOE11154 )

The module aims at introducing students 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

Further information

Decision-making with Analytics ( SOE11166 )

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.

Further information

Digital Analytics Strategy ( MKT11110 )

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.

Further information

Final project development ( SOE11169 )

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.

Further information

Machine Learning, AI and Ethics ( SOE11165 )

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.

Further information

Predictive Analytics ( SOE11167 )

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.

Further information

Prescriptive Analytics ( SOE11168 )

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.

Further information

Skills for Success ( TBS11108 )

Module is designed to ensure all TPG students 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 enhanced student experience for those with identified skills gaps, and provide more skills balances for all students within individual cohorts

Further information

* These are indicative only and reflect the course structure in the current academic year. Some changes may occur between now and the time that you study.

Entry requirements

What are the entry requirements for Business Analytics?

The entry requirement for this course is a Bachelor (Honours) Degree at 2:2 or above in a degree with significant quantitative component. Suitable fields include: Statistics, Psychology, Maths, Physical and Biological Sciences, Business Management, Economics, Finance, Engineering, Computer Science.

We may also consider lesser qualifications if you have sufficient professional work experience within the industry.

Can I get admission into Business Analytics based on my working experience in this sector?

This course has academic entry requirements which are assessed alongside relevant work experience. Full details of any relevant work experience, including references should be submitted with your application and may be considered for entry where the minimum academic entry requirements are below those required.

Usually, unrelated work experience is not considered sufficient for entry without meeting the minimum academic entry requirements. Please contact us with your specific circumstances by submitting an enquiry form above and we will be happy to discuss your options.

Can I make an appointment with an advisor to discuss further about the admission process?

If you want to get more information on the admission process, please get in touch with the postgraduate admissions team by submitting an enquiry form above.

If your first language isn't English, you'll normally need to undertake an approved English language test and our minimum English language requirements will apply.

This may not apply if you have completed all your school qualifications in English, or your undergraduate degree was taught and examined in English (within two years of starting your postgraduate course). Check our country pages to find out if this applies to you.

We welcome applications from students studying a wide range of international qualifications.
Entry requirements by country

Please note that international students are unable to enrol onto the following courses:
  • BM Midwifery/MM Midwifery
  • All Graduate Apprenticeship courses.

See who can apply for more information on Graduate Apprenticeship courses.

We’re committed to admitting students who have the potential to succeed and benefit from our programmes of study. 

Our admissions policies will help you understand our admissions procedures, and how we use the information you provide us in your application to inform the decisions we make.

Undergraduate admissions policies
Postgraduate admissions policies

Fees & funding

The course fees you'll pay and the funding available to you will depend on a number of factors including your nationality, location, personal circumstances and the course you are studying. We also have a number of bursaries and scholarships available to our students.

Tuition fees
Students from 2024/25 2025/26
Scotland, England, Wales, Northern Ireland, and Republic of Ireland £8,715 £tba
Overseas and EU £18,800 £tba
Please note tuition fees are subject to an annual review and may increase from one year to the next. For more information on this and other Tuition Fee matters please see Frequently Asked Questions about Fees Click this link for Information of Bursaries and Scholarships
The University offers a 20% discount on Postgraduate Taught Masters programmes to its alumni. The discount applies to all full-time, part-time and online programmes. The discount can only be applied to year one of a full-time Postgraduate degree, any additional years are exempt from the discount. For part time Postgraduate degrees the discount will apply to years one, two and three only and any additional years will be exempt from the discount.
Please note that the tuition fees liable to be paid by EU nationals commencing their studies from 1 August 2021 will be the Overseas fee rate. The University offers a range of attractive Tuition Fee bursaries to students resident in specific countries. More information on these can be found here.


Careers

What opportunities are there for a graduate with a Business Analytics qualification?

As the influence of data analysis methodology grows, and the volume of data collected increases rapidly, the number and variety of roles in data science are also growing significantly. The purpose of our MSc Business Analytics is to develop industry-ready analytics professionals who have knowledge and skills in the techniques that are integral to developing and implementing the analytics function of organisations, making graduates attractive to employers. (In the Scottish Employer Skills Survey (Scottish Government, 2021) complex analytical skills accounted for 44% of skill-shortage vacancies.)

Graduates will have gained useful and practical business and descriptive, prescriptive and predictive analytics skills and knowledge. This will enable them to significantly contribute to the performance of any organisation and to deliver important information for key business decisions and business development within the global business environment.

Additionally, the program will develop software and modelling skills for implementing analytics projects, including the use of tools that are widely used in the analytics industry such as Python, R, Excel-based modelling, and Simul8.