Business Intelligence and Data Analytics

Data is considered “the oil” of the 21st century, and analytics its combustion engine. Businesses and organisations are increasingly realising the high value of the information hidden in the mounds of data collected and stored. They are investing growing levels of resources to discover the insights hidden in their data through the application of data mining and analytics techniques. Businesses and organisations use such insights combined with business intelligence to detect changing preferences in customer behavior, as well as other emerging trends, thereby increasing their competitive advantage and long-term sustainability.

In today’s analytics economy, in which data science is increasingly adopted by companies across all industries, the demand for data and tech-savvy employees is far exceeding the available supply and thus companies struggle to recruit the required talent for their business intelligence and data analytics.

The MSc in Business Intelligence and Data Analytics is designed to equip the participants 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 participants 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.

Why CIIM MSc in Business Intelligence & Data Analytics

Skills Acquisition: Participants acquire the necessary knowledge, skills and practical experience for the entire data science lifecycle. Participants will undergo the data-scientist transformation as to be in a position to compete successfully in the digital economy.

Practical: The program is delivered from experienced faculty drawn from leading universities and practitioners with an extensive professional experience in the data science field. Particular emphasis will be given to learning and practicing with state-of-the-art tools and programming libraries used in the areas of data-storage and processing (including Big Data), as well as computational statistics and machine learning-based techniques.

International: A state-of-the-art curriculum is taught by world-class faculty with international business experience as advisors, consultants and practitioners; the international dimension is further enhanced by collaborations with leading world universities which are world leaders in the area.

Flexibility: The distinct features of the programme, rolling-admission, flexible start dates, modular structure and modern learning techniques, enable you to obtain the qualification you need for your career development while balancing needs of life, work, and study.

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.

Admissions 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.