This module provides students with the essential tools and techniques to work with data in a business context. You’ll gain hands-on experience with key programming languages used in analytics — SQL and Python — and learn how to prepare, manage, and analyse structured data.

Key topics include:

• Designing and interpreting Entity-Relationship Diagrams
• Using SQL to extract and manage data from databases
• Learning the basics of Python programming and working with popular libraries
• Cleaning, preparing, and exploring data
• An introduction to classical machine learning techniques

You’ll also explore the ethical and legal considerations of working with data, including issues like data privacy, algorithmic bias, and GDPR compliance.

Learning is supported by practical examples from real business environments and access to online training through Kubicle on tools like Python and SQL.

This module builds a strong foundation for anyone looking to work in data-driven roles.

This practical module equips students with essential statistical methods for Business Analytics and focuses on interpreting results, evaluating model performance, and communicating insights to support effective decision-making.

What You’ll Learn:

• How to understand and work with data using graphs, descriptive statistics, and correlations
• Key statistical techniques, including A/B testing, hypothesis testing, and linear regression
• The difference between correlation and causation
• A smooth transition into the basics of machine learning
• How to use Excel for statistical analysis
• How to communicate insights clearly through data storytelling and visualisation

Students will gain hands-on experience with Power BI, creating interactive dashboards and professional reports that bring data to life. They’ll also use DCU’s VR Lab to enhance their presentation skills in a realistic business setting.

The module is grounded in real-world business scenarios and case studies, aligned with UN Sustainable Development Goal 8: Decent Work and Economic Growth.

Additional Learning Support: Students will also access online training via Kubicle, including Data Literacy, Excel for Data Analytics, Data Presentation Skills and Power BI.

This module helps students become confident in working with data and communicating insights in a business context — a vital skill set for today’s data-driven workplace.

Successful leaders need to be able to interpret and make sense of discreet and seemingly unrelated data and events. The objective of this model is to develop your strategic thinking skills in order to

(a) recognise interdependencies, inter-relationships and patterns, and

(b) make consequential decisions using both analysis and intuition, in highly dynamic environments, across different time frames, and different perspectives, both individual and organisational.

The module will provide you with skills, concepts, frameworks, and tools that are useful for developing a strategic mindset including framing and reframing, critical reflection, and systems thinking. A particular emphasis will be placed on forecast and foresight methodologies.

This module explores what it means to conduct research, with the overarching objective to support students in critically evaluating research designs, methodologies and methods appropriate to different research/applied research questions.

This includes devising a research question, conducting a literature review, individual research methods (and how they might work together) and academic writing skills.

In today’s data-rich business environment, organisations must turn vast and complex datasets into meaningful insights. This module builds on core analytics skills developed in the first semester and equips students with advanced tools and techniques to manage, analyse, and communicate data-driven insights effectively.

What You’ll Learn:

• Project and Data Management Fundamentals, including key frameworks like PRINCE2 and Data Lifecycle Management
• Problem-framing strategies using industry-recognised approaches such as CRISP-DM
• Big data concepts, including the use of Hadoop and real-world datasets for practical application
• Unsupervised learning related topics such as dimensionality reduction (PCA, LDA, t-SNE), clustering (e.g., hierarchical and partitional clustering).

The module also explores cutting-edge developments in artificial intelligence:

• Natural Language Processing (NLP), including BERT
• Deep learning and Generative AI, including the use of large language models (LLMs)

Students will also explore the ethical implications of generative AI, focusing on how responsible and inclusive design can contribute to sustainable development goals.

This module prepares students to work confidently with large-scale and complex datasets, using advanced analytics and AI to solve business problems and drive innovation.

This module explores the key challenges involved in managing an organisation at a strategic level. It’s designed to develop students’ ability to think strategically, understand complex organisational dynamics, and lead effectively in changing business environments.

What You’ll Learn:

• How to analyse the business environment and internal capabilities
• Key concepts in leadership, resource allocation, and strategic planning
• How to manage through mergers, acquisitions, turnaround, and decline
• The role of human resources and managerial infrastructure in strategy
• How to engage with socio-political stakeholders at a corporate level

A strong focus is placed on using data and analytics to support strategic decisions. Students will explore structured approaches to strategic analytics, learning how data can drive impactful, sustainable business outcomes aligned with the UN Sustainable Development Goals (SDGs).

Delivered through interactive case studies and real-world business problems, using theory and evidence, you will learn to align data-driven insights with strategic and ethical goals.

This module is ideal for students aiming to lead in complex, high-impact roles across industries where strategic thinking and leadership are critical.

This module focuses on the strategic challenges faced at the business unit level, helping students understand how firms set and achieve their goals within specific markets or industries.

Using a challenge-based learning approach, students will work in teams to solve real-world business problems, enhancing their ability to think strategically, plan effectively, and innovate with purpose.

Key Features:

• Emphasis on innovation and new venture planning
• Collaborative, hands-on projects and workshops
• Mentor-led activities that build practical, career-ready skills
• Strong focus on strategy execution within a business context

Students will develop the tools and mindset needed to drive growth and innovation within organisations, preparing them for strategic roles in dynamic and fast-paced environments.

This module helps students showcase their Business Analytics skills to future employers by creating a professional e-portfolio using GitHub. The portfolio highlights key projects completed throughout the programme and demonstrates students’ ability to apply analytics to real-world business challenges.

What You’ll Create:

• Projects using SQL and/or Python
• Applications of advanced statistics or machine learning
• A Power BI dashboard (e.g., KPI tracking)
• Business-focused summaries with actionable recommendations
• At least one project aligned with the UN Sustainable Development Goals (SDGs)

Students will present their work clearly and professionally, with a focus on how analytics can drive business decision-making and impact.

Delivered through Challenge-Based Learning (CBL): hands-on, project-driven, and practical

Expert guest speakers will cover topics like Regulation and Information Risk; Data Security and Ethics; Sustainable Analytics

Access online training via Kubicle on topics such as GDPR; Data Security; Data Ethics & Risk

By the end of this module, students will have a polished e-portfolio that highlights their expertise and readiness for data-driven roles in the business world.

Dissertation

Students will engage in the steps necessary to execute a research dissertation. Students learn how to identify an applied issue in organisational life which requires research and understanding. This will offer the participant the opportunity to identify, diagnose and investigate this issue.

This includes:

(1) the positioning of the research in the relevant theoretical/empirical literature;

(2) the design of an ethically cogent and methodologically robust research plan, and

(3) the operationalisation of the research programme and the appropriate analysis and interpretation of the data.

The emphasis being on the inclusion of practical and actionable recommendations for change and the demonstration of improvement or enhancement of current organisational practice. Students are required to demonstrate a critical evaluative approach and to undertake empirical investigation and analysis using advanced analytical techniques.

Applied Consultancy Projects

Students work in teams on a major analytics project designed to tackle a real-world business challenge. Projects are grounded in Challenge-Based Learning (CBL), encouraging critical thinking, collaboration, and innovation in real-world contexts.

The projects, which may be sponsored by external clients, typically require feasibility studies followed by creation of an analytics plan, sourcing and preparing data, selecting an appropriate technique, developing and testing a model, communicating the results to the client, and potentially, though not necessarily, operationalising the model.

The Applied Consultancy Project allows students to apply the knowledge and tools gained throughout the programme in a practical setting, while building vital skills in project management, research, and team collaboration.

By engaging with real clients and real data, students bridge the gap between academic learning and professional practice—delivering insights that can create genuine business impact.