Admission Requirements

  • Bachelor’s degree from an accredited program
  • Proficiency in English
  • Success in personal interview

Graduation Requirements

To graduate with an MSc in Business Intelligence and Data Analytics participants need to complete successfully 90 ECTS credits as follows:

  • 78 ECTS from taught core courses (including final project)
  • 12 ECTS either from specialisation courses or by combining courses across.

Programme Table

Core Courses: Total 78 ECTS

Course Code  ECTS
Foundations of Business Information Technology BI395 6
Database Management and Cloud Computing BI405 6
Data Mining, Visualization and Decision Making BI410 6
Managing Big Data BI415 6
Programming for Business Analytics BI420 6
Information Security Management for Business BI425 6
Web & Social Media Analytics BI130 6
Management of Information Systems BI400 6
Quantitative Methods & Statistical Analysis BI430 6
Digital Marketing MA650 6
Ethics, CSR & Sustainability HR495 3
Data Protection: Legal & Ethical Dimensions BI450 3
 Research Methods for Final Project BI440 3
 Data Science Research Project BI500 9

Specialisation Tracks

Operations & Project Management Code  ECTS
Project Management HR465 6
Operations Management & Logistics MA440 4.5
Blockchain Technologies Workshop BI435 1.5

Total 12 ECTS

Entrepreneurship & Innovation Code  ECTS
Entrepreneurship & Innovation MB615 3
Financing New Ventures FB585 3
Business Ventures: From Idea to Execution MB725 6

Total 12 ECTS

Financial Services  (selection 2 of 3) Code  ECTS
Corporate Finance MB405 6
Investment and Portfolio Management FB540 6
Derivatives & Financial Engineering FB530 6

Total 12 ECTS

Marketing Management Code  ECTS
Communication Skills HR535 3
Digital Marketing Project MA651 4.5
Marketing Management MA490 4.5

Total 12 ECTS

Learning Outcomes

A. Knowledge and Understanding

  1. Demonstrate understanding the value of (Big) data, the probabilistic nature of data-driven decision making and the challenges involved in using data analytics to improve business decisions, as well as the ethical and social responsibilities linked to their application.
  2. Identify the basic concepts that underpin today’s organizational IT infrastructures like concepts of databases, information systems, operations and processes, cloud computing, data warehousing and enterprise resource planning.
  3. Demonstrate understanding of information security concepts, challenges, including ethical dilemmas associated and techniques to mitigate them.

B. Intellectual Skills

  1. Integrate concepts and theories behind data mining/analytics (statistical and machine-learning) in order to solve real-world business problems.
  2. Assess the applicability of business intelligence and data analytics techniques used to collect, process, analyze, and interpret data in different contexts.
  3. Develop skills related to data analytics pipeline from collection, processing, analysis and interpretation.

C. Practical Skills

  1. Apply data analytics concepts, theories and techniques to enhance the decision making capabilities.
  2. Develop critical thinking skills by conducting research in the areas of data analytics/mining and business intelligence.

D. Key Transferable Skills

  1. Effectively communicate to top management the results and implications arising from data analytics, security risk assessments, and emerging technologies.
  2. Demonstrate professionalism and leadership by taking initiatives within their domain of responsibility while working effectively with other team members.
  3. Demonstrate the ability to engage in lifelong learning and professional development.
  4. Prepared to take reasonable risks in decision making and treat failures as learning opportunities.