- Bachelor’s degree from an accredited program
- Proficiency in English
- Success in personal interview
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.
Core Courses: Total 78 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|
|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|
|Operations & Project Management||Code||ECTS|
|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|
|Investment and Portfolio Management||FB540||6|
|Derivatives & Financial Engineering||FB530||6|
Total 12 ECTS
A. Knowledge and Understanding
- 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.
- 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.
- Demonstrate understanding of information security concepts, challenges, including ethical dilemmas associated and techniques to mitigate them.
B. Intellectual Skills
- Integrate concepts and theories behind data mining/analytics (statistical and machine-learning) in order to solve real-world business problems.
- Assess the applicability of business intelligence and data analytics techniques used to collect, process, analyze, and interpret data in different contexts.
- Develop skills related to data analytics pipeline from collection, processing, analysis and interpretation.
C. Practical Skills
- Apply data analytics concepts, theories and techniques to enhance the decision making capabilities.
- Develop critical thinking skills by conducting research in the areas of data analytics/mining and business intelligence.
D. Key Transferable Skills
- Effectively communicate to top management the results and implications arising from data analytics, security risk assessments, and emerging technologies.
- Demonstrate professionalism and leadership by taking initiatives within their domain of responsibility while working effectively with other team members.
- Demonstrate the ability to engage in lifelong learning and professional development.
- Prepared to take reasonable risks in decision making and treat failures as learning opportunities.