Program Overview

Business Analytics - MSc

Brief Description

Develop your business and quantitative analysis skills to solve complex business problems, communicate your findings, and implement strategies. UL's one-year, full-time Master of Science in Business Analytics programme gives you the skills and knowledge to engage with business problems using large data sets, statistical methods, optimisation techniques, and predictive models.

Overview

During this programme, you will:

• Learn how to use business analytics to solve problems and make smart, well-rounded decisions that consider all areas of a business.
• Build critical thinking and decision-making skills using both numbers (quantitative tools) and context (qualitative insights).
• Develop leadership and teamwork skills, like emotional intelligence, curiosity, and strategic thinking, that are essential for managing people and driving change.
• Cultivate a strong sense of ethics and responsibility, encouraging graduates to make a positive impact on society and the business world.

Programme Content

Key Information

• Complete full-time over one year
• Modules taught during autumn, spring, and summer semesters
• In the first semester, you will develop strong quantitative skills
• In the second semester, you will learn how to apply these skills to real-world business contexts
• In the summer semester, you will apply your skills to complex scenarios with our innovation lab and simulation modules
• Option to exit with Graduate Diploma after spring semester
• Option to pursue a dual degree with a choice of five prestigious French business schools

You will learn through a blend of:

• Lectures, workshops, and hands-on activities
• Regular feedback from faculty and peers

Year 1

Autumn Semester

• Data and Analytical Decision Making (MI6201) will examine how data analysis technologies can be used to improve decision-making and the changing nature of decision making in an organisational context.
• Statistics for Data Analytics (MA6101) is a module focusing on data collection, visualization, probability distributions, hypothesis testing, correlation, and regression models for predictive analytics.
• Database Systems in Practice (CS6401) aims to introduce the relational data model alongside NoSQL data models with an emphasis on the development of practical skills for work with database management systems.
• Machine Learning & Applications (CS6501) equips students with an understanding of the key principles and methods in the field of Machine Learning.
• Project Management in Practice (MN6041) provides the knowledge, skills, and understanding to apply project management principles, tools, and techniques to deliver value to the organisation.

Spring Semester

• Data Governance & Ethics (IN6062) provides a conceptual framework relating to ethics and governance that informs data analytics activities and research.
• Applied Econometrics for Business (EC6062) covers a range of techniques widely used in modern applied econometric work and demonstrates how they are applied to specific areas of economic enquiry.
• Digital Organisations, Markets & Consumers (MK6102) introduces you to the complexities and dynamics of digital markets, organisations, and consumers.
• Applied Big Data & Visualisation (CS6502) serves as an introduction to big data management and associated issues.
• Leadership, Influence & Change (PM6072) examines the nature of leadership and how it is linked to organisational culture and change management.

Students have the option to exit with a Graduate Diploma in Business Analytics.

Summer Semester

• Digital Futures Lab (MI6103) uses a design approach to address complex organisational and societal problems through mapping, analysis, and creative thinking.
• Business Simulation (MI6303) provides an interactive, self-directed, experiential learning experience, engaging and developing students in strategic decision making.

Entry Requirements

• Applicants should hold a bachelor's degree (NFQ Level 8) with at least a second-class honours, grade 2 (2:2) in a relevant discipline e.g., business, finance, economics, mathematics, engineering, computer science, etc.
• Other Entry Considerations: We encourage you to apply even if you don't meet the standard entry requirements, as long as you can show that you have the knowledge, skills, and experience needed for the programme.
• International students: For details on country-specific qualifications, visit postgraduate entry requirements for international students.
• Checklist of Documents:
  • Academic transcripts and certificates
  • Copy of your birth certificate or passport
  • English translation of your qualifications and transcripts
  • Copy of your CV
• English Language: English Language Competency certificate. For details on accepted language qualifications, visit English Language Requirements.

Fees

• EU: €12,200
• Non-EU: €20,400
• Annual fees are billed by semester. Once registered, students may be eligible to apply for a monthly payment plan.
• Further information on fees and payment of fees is available from the Student Fees Office website.

Funding

Find further information on funding and scholarships.

Graduate Profile

This course can lead to the following sectors and careers:

• Business analyst
• Financial Analyst
• Quantitative Analyst
• Management Consultant
• Data Analyst
• Data Scientist
• Project Manager
• Supply Chain Manager
• Research Analyst