MSc in Business Intelligence and Data Analytics
Program Overview
The Master of Science (MSc) in Business Intelligence and Data Analytics is designed to equip the students with the necessary knowledge and a diverse set of skills required throughout the data analytics lifecycle. This skillset includes business data requirements, data acquisition and integration, data storage, data processing, data analysis, insights derivation, and ultimately, the business deployment of derived insights in a meaningful and successful manner.
It is a unique and innovative-by-design postgraduate degree that combines both managerial and technical aspects around the data science field. Particular emphasis is given to students acquiring practical skills for implementing data science solutions, as well as enhancing their decision-making capabilities in Information Technology from a data science perspective.
The curriculum is designed to transform the participants into data scientists and equip them with the knowledge and skillset required to contribute and compete in the rapidly advancing data-driven economy.
MSc in Business Intelligence and Data Analytics Program includes:
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The program is nationally accredited by CYQAA and recognized by KYSATS.
Admissions Requirements
- Bachelor’s degree and transcripts from an accredited program. In terms of GPA, we expect 2:2 and above from UK schools, 3.0 and above from US schools, and 6.5 and above or the equivalent from Cypriot and Greek Universities and colleges. Candidates with a lower grade than the above, might be admitted if they have compensatory strengths in terms of work experience or other accomplishments (for example, CFA, ACCA, or ACA).
- Native speaker of English or graduate of a high school or university where the language of instruction is English, or IELTS with a score of at least 5.5, or TOEFL with a score of at least 250 (computerized) or 550 (conventional), or Password-plus 5.5.
- Satisfactory quantitative skills as evidenced by the quantitative courses they have taken during their Bachelor’s degree study.
- Knowledge of English language. Click here to learn more.
Program Learning Outcomes
- Demonstrate understanding the value of (Big) data and data driven decision making.
- Identify the basic concepts that underpin today’s organizational IT infrastructures, such as concepts of databases, information systems, operations and processes, cloud computing, data warehousing and enterprise resource planning.
- Apply data mining/analytics (statistical and machine-learning) in order to solve real-world business problems.
- Develop skills related to data analytics pipeline from collection, processing, analysis and interpretation.
- 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.
Program Requirements
The European Credit Transfer and Accumulation System (ECTS in short) is a tool of the European Higher Education Area for making studies and courses more transparent. It helps students to move between countries and to have their academic qualifications and study periods abroad recognized. The credits below are based on the ECTS.
To graduate, students are required to earn 90 credits as follows:
78 credits from taught core courses (including final project),
12 credits either from one of the three concentration tracks, or by combining courses from different tracks.
Core Courses
- BI395 – Foundations of Business Information Technology
Contact Hours: 28 Credits: 6 - BI405 – Database Management and Cloud Computing
Contact Hours: 28 Credits: 6 - BI410 – Data Mining, Visualization and Decision Making
Contact Hours: 28 Credits: 6 - BI415 – Managing Big Data
Contact Hours: 28 Credits: 6 - BI420 – Python Programming
Contact Hours: 28 Credits: 6 - BI425 – Information Security Management for Business
Contact Hours: 28 Credits: 6 - BI130 – Web & Social Media Analytics
Contact Hours: 28 Credits: 6 - AT600 – Digital Transformation of Business & Organizations
Contact Hours: 28 Credits: 6 - BI430 – Quantitative Methods & Statistical Analysis
Contact Hours: 28 Credits: 6 - AT500 – Data Analytics and Artificial Intelligence
Contact Hours: 28 Credits: 6 - HR495 – Ethics, CSR & Sustainability
Contact Hours: 28 Credits: 6 - BI500 – Data Science Research Project
Contact Hours: 28 Credits: 12
Elective Courses
- MB675 – Operations & Supply Chain Management
Contact Hours: 28 Credits: 6 - MB710 – Project Management
Contact Hours: 28 Credits: 6 - AT800 – Project Management in Information Technology
Contact Hours: 28 Credits: 6 - AT400 – Blockchain and Applications
Contact Hours: 28 Credits: 6
- AT900 – Technical Entrepreneurship
Contact Hours: 28 Credits: 6 - GD320 – Digital Business Tools and Digital Business Development
Contact Hours: 28 Credits: 6 - FB415 – Project & Business Financing
Contact Hours: 28 Credits: 6 - MB750 – Planning & Starting a New Business
Contact Hours: 28 Credits: 6
- FB470 – Innovative Financial Technologies (FinTech)
Contact Hours: 28 Credits: 6 - FB500 – Financial Innovation and Financial Regulation
Contact Hours: 28 Credits: 6 - FB415 – Project & Business Financing
Contact Hours: 28 Credits: 6 - GD320 – Digital Business Tools and Digital Business Development
Contact Hours: 28 Credits: 6 - AT400 – Blockchain and Applications
Contact Hours: 28 Credits: 6
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English (UK) 
Ελληνικά