Curious about studying Business Management with Analytics - BA (Hons)at Abertay University? We've gathered all the key details—entry requirements, modules, fees, and more. Hear from real students by checking out reviews, or take the next step by booking an open day to explore it for yourself.
Bachelor of Arts (with Honours) - BA (Hons)
Abertay University
Full Time
Sep 2026
4 Year
Study business analytics and learn new, powerful digital tools and analytical skills that are in great demand across the world. Join this Business Management with Analytics degree at Scotland’s Top Modern University for Student Satisfaction (CUG2027) and kick-start your career.
As organisations collect more Big Data, they need talented employees who can analyse that data strategically in areas such as marketing intelligence, CRM, sales and financial management. We will help you to excel in a range of business settings, so you can influence and make informed, data-driven business decisions.
Outstanding business links and valuable work placements'Business Analytics' means you can harness powerful tools using skills that are in great demand across the business world. Focussed clearly on employability, there are work placement options and you can apply to study abroad. You'll learn to present and interpret findings clearly and effectively. Your ability to clearly identify business opportunities will mesh perfectly with the ever-changing job market. When you graduate you will be ready to improve organisational productivity, performance and profits. Whether your ambition is to start your own business or work within an organisation, your skills will be relevant all over the world.
Scotland’s Top Modern University for Student SatisfactionAbertay is widely regarded as THE place to come for student satisfaction and high quality teaching. But don't take our word for it: *
Scotland's Top Modern University for Student Satisfaction(The Complete University Guide 2027 and Times Good University Guide 2026). *
UK Top 10 for Student Experience(The Times Good University Guide 2025 and The Daily Mail University Guide 2024). *
Top Scottish Modern University(Guardian University Guide 2026).
This module builds on your existing knowledge of human resource management and deepens your understanding of HRM theory and practice. You will explore how HRM principles are applied in contemporary organisations, examining both strategic and operational perspectives, and develop the skills to critically evaluate HRM approaches in real'world contexts. Indicative content - Introduction to HRM : Theoretical perspectives to HRM; practical approaches to HRM. - Context and HRM: National, international, occupational, organisational and individual contexts of HRM in theory and in practice. - Strategic HRM: I ntroduction to strategic human resource management; ‘best fit’ and ‘best practice’ approaches. - HRM, work and wellbeing: Fair work; dignity at work; mental health and stress at work; the benefits and challenges of flexibility. - HRM, equality and diversity: Inequalities in the labour market and in the workplace; managing diverse workforce. - Managing conflict in the workplace : Conflict in the employment relationship; misbehaviour, discipline and grievance procedures; bullying and harassment; disputes. - Contemporary HRM trends and future challenges: Continuity and change in work and employment; gig economy; (ir)responsible HRM.
This module introduces the core principles of business analytics, focusing on descriptive and predictive approaches. Designed for students with or without prior higher'level study in statistics, it builds on introductory concepts to develop practical skills in analysing and interpreting data. You will learn how to summarise and visualise information, identify patterns and trends, and apply predictive techniques to support effective decision'making in business contexts. Indicative content - Control and Quality of Decisions: Explore whether decision'making is rational or emotional, what makes for a good decision, and whether it is an art or a science. Study the role of data and information, the characteristics of good information, and the applications of big data and analytics, including their use in the finance function to create organisational value. - Basic Business Data Analysis Using Excel: Apply digital technologies in the finance function to demonstrate trends and patterns, prepare trend equations using graphical methods or regression analysis, and evaluate the limitations of forecasting models. - Business Decision'Making in Practice: Examine the opportunities and challenges of emerging technologies in business, review the key features of data protection and privacy regulations when handling data, and engage with business simulations to apply decision'making in realistic contexts.
The module aims to develop your awareness of the business challenges associated with sustainable business creation and development, and to provide you with the knowledge and skills required to make a convincing case for investment in a sustainable business idea. Indicative content - People: Beautifying Business − Opportunity or gimmick: Managing the triple bottom line; Business boundaries, doing more with less; strategies for sustainable business development; Business and the planet; Sustainable entrepreneurship and new business models, Corporate social responsibility - Profit: Ethical investing and responsible investment: Responsible investment and the cost to society and the individual. - Planet: Environment, enterprise and innovation: Wealth from Waste… Students will be encouraged to consider opportunities for innovation which identify revenue streams arising from re−use of waste materials - Energy Enterprise: Ideas and innovation which maximise current energy sources or innovate in the realm of renewable energy production/storage/delivery; Planet Premium and Ecosystem Services… acknowledging and valuing benefits and services delivered by the natural environment. Payment for ecosystem services, willingness to pay.
Please note: If you are a Direct Entrant (new student) to this year of study and have not previously taken module ABE101, then you MUST take ABE201 as your Term 2 microcredential module. If you have previously taken ABE101, then you are NOT permitted to take ABE201 in Term 2. Starting university brings new opportunities and challenges, and every student’s journey is different. This microcredential helps you settle into life at Abertay and build the habits that lead to success. You’ll hear from current students sharing their own tips, and reflect on the areas you most want to develop. You’ll get to know Abertay’s systems, explore what makes a successful student and practise core skills such as time management, referencing, academic writing style and using support services. By the end, you’ll have the tools and strategies you need to thrive at university. Indicative content - Navigating Abertay Systems: Get to know the key systems you’ll use at Abertay—such as MyLearningSpace, MS Teams, OASIS and MyAbertay—and learn how to use them effectively. - Expectations of University and You: Explore what’s expected of you as a student and what you can expect from the university. Topics include the code of conduct, independent and blended learning, how courses are structured, health and safety, and the Abertay attributes. - Abertay Discovery Tool: Complete the Discovery Tool to identify your strengths and areas for development across five themes: studying at university, academic skills, digital skills, careers and employability, and wellbeing. - Fundamentals of University: Learn how modules work, how assessments are set, and how to use assignment briefs and feedback to improve your work. - Understanding, Searching and Evaluating Information: Develop strategies for finding and assessing reliable information, building your confidence in research and study skills. - Successful Student Behaviours: Practise the habits that help you succeed: managing time, avoiding procrastination, effective note-taking, preparing for classes, developing a growth mindset, and making use of student support services. - Referencing: Understand academic integrity and why referencing matters. Learn how to avoid plagiarism, create in-text citations and reference lists, and use digital tools to manage your sources. - Sounding Academic: Discover what lecturers mean by “academic style” and how to use the right language in your writing. Learn the rules of academic writing, how to paraphrase effectively, and how expectations differ between school/college and university. You’ll also explore how assessments, marking and feedback work.
The tools and techniques associated with managing projects. You will carry out an investigation into a project failure and recommend alternative actions which could have been taken. Indicative content - Project management and project teams: Interpreting project specifications and objectives, and the requirements of project stakeholders; Key project challenges for individuals and groups: reviewing the key priorities of time and project management; Understanding the role of a project leader; Understanding team work and how effective teams function; Creating and contributing to effective project teams; Managing teams through project delivery; maintaining goal focus, and managing problems. - Project analysis and planning: Analysing project requirements and sub-tasks; Estimating timelines; deadlines and milestones and activity durations; Constructing a project schedule; Resourcing projects; Allocating and smoothing resources; Using Gantt charts to allocate and monitor resource allocation; Project management tools; Using project management software. - Managing projects: Dealing with project risk; Evaluating the probability and potential impact of risk; contingency planning for risk management; project tracking and revision to completion; Evaluating project delivery and management: Analysing the effectiveness of project management processes and the impact of project delivery and non-delivery. - Project management methodologies: Understanding the use of project management methodologies such as Prince2 and SCRUM; their benefits and challenges; adjusting your methodology to the size of the project.
This module explores the concept and practice of digital transformation, understood as the fundamental rewiring of how organisations operate to create value through technology at scale. You will examine how digitalisation drives value creation both through the development of new digital products and the transformation of existing business processes. Emphasis is placed on the change process involved in becoming digital, alongside the organisational, strategic and cultural outcomes that digitalisation must deliver. By the end of the module, you will have a critical understanding of how digital transformation reshapes business models, operations and value creation in contemporary organisations. Indicative content - Meaning and Scope of Digital Transformation: Introduction and overview of current trends and issues, and the goals of digital transformation. - Digital Platforms and Technologies: Explore how digital platforms create value, and examine the role of AI, Big Data and Business Intelligence in shaping organisational impact. - Approaches to Digital Transformation at an Organisation: Learn how to get started by setting goals, identifying competencies and resources, and creating an implementation framework for transformative value. - Digital Innovation: Analyse successful and unsuccessful examples of digital innovation, their impact on organisational transformation, and approaches taken by both large and small organisations, including strategies for imitation and protection. - Deriving Value from Social Media: Investigate how digital platforms can optimise customer relationship management and strengthen engagement. - Digital Transformation and AI: Understand the value AI can deliver for organisations, with examples of its utilisation in digital transformation. - Dealing with Disruptive Innovations: Examine disruptive innovation, barriers to imitation, and strategies for successful adaptation. - Benefits and Risks of Digital Transformation: Identify and maximise the benefits of digital transformation for organisations and stakeholders, while recognising and mitigating associated risks.
In this module, you will gain critical insights into consumer behaviour and explore why understanding consumers is essential for contemporary organisations. You will learn how to apply market research methods and analytical tools to build this understanding, while engaging with key consumer behaviour theories and concepts. You will also develop knowledge of market research design and data analysis, enabling you to support effective decision'making in organisational contexts. Indicative Content - Fundamentals of Consumer Behaviour: Explore decision'making models and the factors that influence consumer choices, including needs, motivation and values. Examine perception, memory and learning, attitude theory, and theories of personality, self and identity. Analyse the role of social and group influences on consumer behaviour, as well as the impact of digital environments on consumer decision'making. - Principles of Marketing Research: Learn how to design marketing research projects and identify researchable questions. Understand the importance of data and data'driven decision'making in marketing. Develop knowledge of primary research methods, including quantitative and qualitative data collection techniques, alongside secondary research approaches and issues of data quality. - Data Analysis: Gain skills in qualitative data collection and analysis, such as discourse analysis, and apply quantitative data collection and analysis methods, including the use of secondary data, to support marketing insights.
In this module, you will explore established graduate employability frameworks and investigate how to apply them to your own career development. You will learn how to align your skills, knowledge and experience with the expectations of prospective employers, enabling you to identify areas for growth and strengthen your employability profile Indicative content - Understanding Theoretical Frameworks of Graduate Employability: Explore the nature and purpose of modern concepts and frameworks of graduate employability, and how they shape opportunities in the workplace. - Understanding Employers’ Needs: Analyse current trends in your chosen field of employment, examine employers’ requirements for staff, and consider how these expectations evolve over time. - Assessment of Personal Employability: Investigate the range of skills and attributes employers seek in your field, and assess your own employability to identify strengths and areas for development.
This module expands on the material covered in business analytics by providing students with the necessary theory and techniques to perform predictive and prescriptive analytics in a business context. Prescriptive analytics differs from descriptive and predictive analytics in that prescriptive analytics indicates a course of action to take. Indicative content - Predictive Data Mining: In these lectures, we discuss data sampling, preparation and partitioning; performance measures; the logistic regression; and classification and regression trees. - Spreadsheet Models: In these lectures, we learn some useful Excel functions for modelling and construct predictive and prescriptive models. - Monte Carlo Simulation: The goal of these lectures is to introduce students to simulation and apply the techniques learned to specific business cases. - Mathematical Optimization: In these lectures, we cover the main optimization techniques that will be used in the rest of the module. - Linear Optimization Models: In these lectures, we explore linear programming techniques. - Integer Linear Optimization Models: In these lectures, we explore the different types of integer linear optimization models and apply excel solver to find solutions. - Decision Analysis: In these lectures, we study decision analysis with and without probabilities, and decision analysis with sample information.
You'll combine theory and practice to examine organisational change and transformation in times of uncertainty. Indicative content - Analysing change contexts and drivers: The change context: globalisation, technology, and changing market dynamics; change management and sustainability. - Theories of change and approaches to change management: Models of change and change management; transformational change and organisations; Critical discourse in change management. - Human resources issues in change management: Participative change; managing psychological contracts, social identity, stakeholder dynamics; voice, dialogue and rethinking resistances in change; Culture, habits and unlearning. - Change in context: (this will change each year and will form the basis of the guest lectures). - Leading and managing change: Transactional and transformational leadership; values and value-based systems in transformational change.
In this module, you’ll explore how organisations create and sustain competitive advantage in today’s dynamic business environment. You’ll learn about the key concepts, tools and approaches that underpin strategic management, from analysing markets and competitors to making and implementing strategic choices. You’ll also examine how strategy operates within the public sector and consider the challenges of turning strategic plans into effective action. Indicative content - Strategy and the organisation: Understanding of strategy. Strategy, tactics, operations. - The context of strategy: Industry analysis: turbulences and dynamics. Porter’s five forces. - Business level strategy, corporate level strategy, network level strategy: Levels of strategy and sources of competitive advantage. - Generic strategies, hybrid strategy - Strategy as value creation - Strategy in the public sector - Public-private partnership as strategic tool of public sector management
This module introduces you to the principles and practices of operations management — the discipline concerned with turning inputs into outputs efficiently and effectively. You’ll explore key areas including supply chain management, logistics and process improvement. Through theory and practical application, you’ll learn how to evaluate and enhance operations across different markets and contexts, and examine how business process redesign and re-engineering can drive lasting improvements in organisational performance. Indicative content - Operations Management in its Organisational Context: The operations function within the organisation and its relationship with other functional areas; The role of the operations manager. - Introduction to Supply Chain Management: The supply network; designing the supply chain (make or buy); supply chain stages; uncertainly and risk factors, value chain. - Designing the process: Analysing, Designing, Developing, Implementing and Evaluating in business process redesign (The ADDIE Model). - Capacity Management: Demand v. production, models of capacity planning, measuring capacity (utilisation and efficiency calculations). - Inventory Management: Why hold stock? Costs of inventory, ABC analysis, economic order quantity, inventory management strategies. - Digitalisation in Operations Management, supply chain and logistics: Operations 4.0, Supply chain and logistics 4.0, E-supply chain, IT application in supply chain system, enterprise resource planning, technology strategies. - The end-to-end supply chain: Purchasing and supply, materials and distribution management, logistics, balancing flow within a supply chain, managing bottlenecks and restrictions. - Outsourcing: Make or buy decisions in sourcing strategy; supplier selection; outsourcing supply chain management; co- ordinating supply and managing supplier relationships & partnerships, supply chain risks management. - The customer interface: Meeting customer requirements, forecasting demand, lean operations and JIT, lean principles, reducing waste. - Contemporary supply chain dynamics: Supply chain measures, six sigma, strategic alliances and collaborative partnerships, characteristics of supply chains in the contemporary global economy.
This module introduces you to programming languages widely used in the industry for data analysis and machine learning. This is not a module in more advanced programming languages such as C++. Indicative content - Programming, Data Analysis and Machine Learning: Programming as an important tool for the business analyst. - I ntroduction to Programming: Data structures, algorithms and programming languages. - Programming with Python: Python, one of the most widely used programming language for data analysis and machine learning. - Data Analysis and Machine Learning: In these lectures, we use statistical software to develop programmes for data analysis and machine learning.
In this module, you’ll explore the challenges modern businesses face in balancing profit with purpose. You’ll examine how companies are expected to deliver financial performance while also acting responsibly toward stakeholders and the environment. The module will help you understand how sustainability and ethics are reshaping business strategy and decision making. Indicative Content - Conceptualising corporate responsibility: The development of 'corporate social responsibility'; people, equality and justice; diversity and inclusion in the workplace; theorising 'ethical' corporate conduct - Dimensions of corporate responsibility: Corporate criminality; ethical consumerism; ESG investment; environmental sustainability - Key debates in corporate responsibility: Corporate social responsibility: reality or rhetoric? The possibilities and limits of environmental sustainability
D Grades/points required
Not currently available, please Contact University for up to date information.
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