Programme Details

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
Python Programming BI420 6
Information Security Management for Business BI425 6
Web & Social Media Analytics BI130 6
Digital Transformation of Businesses & Organizations AT600 6
Quantitative Methods & Statistical Analysis BI430 6
Applied Artificial Intelligence & Deep Learning AT500 6
Ethics, CSR & Sustainability HR495 3
Data Science Research Project BI500 12

Specialization Tracks

Operations & Project Management (12/24 ECTS) Code ECTS
Operations & Supply Chain Management MB675 6
Project Management MB710 6
Project Management in Information Technology AT800 6
Blockchain and Applications AT400 6
Technical Entrepreneurship & Innovation (12/30 ECTS) Code ECTS
Technical Entrepreneurship AT900 6
Green and Digital Entrepreneurship & Innovation MB615 6
Project & Business Financing FB415 6
Mobile Application Development AT750 6
Planning & Starting a New Business MB750 6
Financial Services (12/30 ECTS) Code ECTS
Innovative Financial Technologies (FinTech) FB470 6
Regulation of Innovative Financial Technologies (RegTech/LegTech) FB500 6
Project & Business Financing FB415 6
Digital Business Tools and Digital Business Development GD100 6
Blockchain and Applications AT400 6

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.
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BIDA Programme Director

“Data is characterised as the oil of the 21st century and the MSc in Business Intelligence and Data Analytics equips the students with all necessary knowledge and diverse skillset to compete in the newly formed digital economy”

Dr. Theodosis Mourouzis
Director of MSc in Business Intelligence& Data Analytics