MSc Data Analytics (Distance Learning)
Delivery & Mode of Study
Language of Instruction
Credits
Factsheet
Introduction
The MSc Data Analytics programme at UCLan Cyprus is the only programme in Cyprus which offers the SAS Joint Certificate. UCLan Cyprus MSc Data Analytics graduates have the option to receive the SAS Joint Certificate in Business Intelligence and Data Mining in addition to their MSc award. The SAS Joint Certificate equips students with additional knowledge and skills to apply analytics to real business problems using real business data and provides students with a competitive advantage in the marketplace, through a professional certification which is in high demand by the market. The combination of the MSc Data Analytics programme and the SAS Joint certificate curriculum prepares graduates to work in a data-rich business environment and have a rewarding career in the digital age.
Data Analytics is the science that allows decision makers to unveil new business insights by examining large amounts of data to uncover hidden patterns, correlations and other important insights.
This course is designed to provide graduates and working professionals with knowledge and a diverse set of skills that span across all layers of the knowledge discovery stack including storage, mining, analytics, decision support frameworks and visualisations, as well as practical experience with modern tools. In particular, students will learn how to:
(i) analyse large data sets and summarise their main characteristics with the use of attractive data visualisations;
(ii) design and create databases that allow organisations to efficiently manage and query their enterprise data;
(iii) discover patterns in large data sets with established techniques from various fields such as statistics, machine learning and artificial intelligence; and
(iv) understand today’s turbulent business environment and learn how modern BI tools enable organisations to survive and excel.
Career Opportunities
This course is designed to provide graduates and working professionals with skills that enable them to organise, analyse, explore, interpret and visualise their data, as well as acquire practical experience with modern tools. These skills can be used in virtually every industry domain that uses data, such as Business, Finance, Banking, Healthcare, Energy, Manufacturing, Technology, Marketing, etc.
Data Analyst
Focus: Analyzing complex datasets to extract meaningful insights, build predictive models, and guide business decisions using statistical and machine learning techniques.
Business Intelligence Analyst
Focus: Transforming raw data into actionable insights that help businesses improve decision-making, enhance efficiency, and develop strategies.
Data Engineer
Focus: Designing, building, and maintaining data pipelines, systems, and architectures to ensure smooth data flow and accessibility for analysis.
Quantitative Analyst
Focus: Using mathematical models and statistical techniques to analyze financial data, assess risks, and optimize investments.
Course Benefits
SAS Joint Certificate
This programme is the only MSc Data Analytics programme in Cyprus which offers the SAS Joint Certificate in Business Intelligence and Data Mining in addition to the MSc award.
Access to Cutting-Edge Tools & Technologies
Students gain hands-on experience with industry-leading tools such as Python, R, SQL, machine learning frameworks, and data visualization software to develop real-world analytics skills.
Flexible & Self-Paced Learning
The distance learning format allows students to study at their own pace and balance their education with work, family, or other commitments.
Industry-Driven Curriculum
The course is designed to meet current market demands, covering big data, artificial intelligence, machine learning, and statistical analysis, ensuring graduates are prepared for modern data-driven roles.
Networking & Industry Connections
Even as a remote student, learners have opportunities to connect with professors, industry professionals, and fellow students through virtual events, online discussions, and collaborative projects.
Pathway to Further Research & Specialization
Graduates can pursue PhD studies, professional certifications (e.g., AWS Data Analytics, Google Data Engineer), or specialized roles in areas like AI, data science, and business intelligence.
Course Visual Content
Programme Modules
Compulsory
Module Code:
CO4820 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- The module aims to develop students’ research, critical analysis and academic writing skills to Masters level.
Module Code:
CO4759 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Apply design techniques to construct an information model.
- Study a relational database management system.
- Study and use the Structured Query Language (SQL)
- Design and develop a relational database according to the requirements of an organisation
Module Code:
CO4761 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Provide an in-depth knowledge of the use of enterprise systems
- Study the type of data that the enterprise systems generate
- Study how that data might be used to support decision making within an enterprise
Module Code:
CO4804 (L7)
Credit Value:
60 UK CREDITS / 30 ECTS
Module Aims:
- To develop the ability to solve complex problems, using appropriate skills and knowledge acquired elsewhere.
- To develop student’s ability to critically reflect on their work and on the work of others.
- To enable students to demonstrate disciplines of time management, project planning and reporting on progress.
- To encourage students to read to discover best practice.
- To develop the ability to apply theory in the real world.
- To foster an attitude of constructive criticism in evaluation.
- To use theory appropriately when communicating about project work
Module Code:
CO4760 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Provide essential exploratory techniques to describe data
- Introduce computational methods for solving statistical problems
- Introduce the R programming language, its packages, statistical functions, plotting systems
- Demonstrate the principles for constructing visual representations of the data
- Evaluate the information discovered from data analysis
Module Code:
CO4762 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Understand the value of knowledge discovery in solving real-world problems
- Understanding of foundational concepts underlying data mining.
- Evaluate important knowledge discovery techniques
- Apply a wide range of knowledge discovery tools to real-world problems.
- Evaluate the processes involved in the creation and maintenance of data warehouses.
Optional
Module Code:
CO4512 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- To introduce information security and risk management standards and methods that students will most likely encounter as a security professional.
- To evaluate the applicability and critically analyse alternatives for information security management and risk assessment.
- To apply techniques and conduct activities involved in the process of information security and risk management.
- To critically evaluate the benefits and pitfalls of compliance-based security.
Module Code:
CO4519 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Demonstrate various AI models and techniques to develop understanding of AI solutions of a range of problems and explore the expected performance of such models
- Practically explore a wide range of AI techniques, which are being applied in industry and/or research.
- To demonstrate an awareness of current and new/future developments in the field of AI and its applications.
- Identify and explore real-world problems and determine which AI approaches are suitable for their solutions.
Module Code:
CO4102 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Discuss the evolution of information systems and their historical role in organizations and importance of systems integration.
- Introduce and discuss the components and architecture of ERP (Enterprise Resource Planning) systems.
- Explore the role of an ERP system in an organization in terms of its efficiency and worker productivity.
- Critically evaluate the implementation process of an ERP system, including ERP selection, selection criteria, success factors and effective programme management
- Identify the ethical, legal, global and security challenges related to ERP systems and implementations and how to protect the company assets.
- Discuss the role and goals of CRM (Customer Relationship Management) systems in the context of ERP.
Module Code:
MD4099 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- This module aims to examine both the strategic and operational decisions that managers must make in order to engage in global activities. By engaging with the theoretical literature and examining international business in action, students will assess the links between globalisation and competitiveness, both at corporate and national levels. As a result students will be able to evaluate the impacts of globalisation and internationalisation. Detailed research into case-studies will also be conducted as a means of explaining the real-time situations they experience.
Module Code:
CO4609 (L7)
Credit Value:
20 UK CREDITS / 10 ECTS
Module Aims:
- Confidence and ability to discuss the use of Communication/Web Technologies in Marketing
- A sound understanding of both theory and practice of online marketing (referred to as e-marketing)
- An ability to make e-marketing decisions using case study material;
- An appreciation of the practical issues concerned with e-marketing
Learning Outcomes
A1. Understand and appreciate the role that an analyst plays in the organizational and development processes of a company.
A2. Develop a systematic understanding of statistical data analysis and data mining techniques used in data analytics and areas of its application.
A3. Describe and evaluate principles, practices and techniques relevant to data mining and decision support.
A4. Develop a practical understanding of different forms of data (unstructured, semi-structured, structured), information modelling and the development of databases.
A5. Critically evaluate skills, tools and techniques necessary for the effective application of data analytics.
A6. Initiate and complete a major piece of individual study independently for a research or industry related topic.
B1. Describe and apply appropriate knowledge of statistical methods, algorithms and quantitative techniques suitable for data analysis and mining in a broad range of application areas.
B2. Specify, design and construct fit for the purposes databases making use of appropriate modelling techniques.
B3. Apply various technologies, techniques tools and methods in the full spectrum of data analytics including databases, data warehouses, distributed data management, data mining and decision support.
B4. Demonstrate the ability to work with software, software packages and software suites in order to automate tasks and perform data analysis.
B5. Conduct an in-depth analysis of a problem using evidence and deliver and present solutions to real-world problems using various visualization techniques.
C1. Evaluate ideas, methods and systems in a coherent and thorough manner, identifying limitations and opportunities for further development.
C2. Integrate, analyse and evaluate data and scenarios, using a wide range of appropriate techniques and transform those into options and solutions.
C3. Analyse and evaluate appropriateness of complex information, methods and techniques related to data analytics issues.
C4. Locate and integrate information from multiple sources and use conceptual, analytical and quantitative skills for decision making.
C5. Formulate solutions to complex problems and use appropriate methods to communicate such solutions effectively to a professional audience.
D1. Develop a highly analytical approach to problem solving.
D2. Effectively work as part of a group or as a group leader.
D3. Communicate effectively in context through presentations and written reports to a diverse audience.
D4. Utilize Information and Communications Technology (ICT).
D5. Develop individual self-management, and independent learning skills and manage resources and time in order to achieve intended goals.
D6. Reflect critically on professional experience, devising and evaluating new approaches.
Entry Requirements
The minimum entry requirements for this programme are:
Requirement 1
Bachelor's degree, with at least Lower Second Class grade or equivalent.
Requirement 2
Proof of English Language knowledge to a score of at least IELTS 6.5, or other equivalent according to the Common European Framework of Reference for Languages (CEFR).
How To Apply?
Step by Step Application Process.
Complete the UCLan Cyprus application FORM.
Provide copies of:
– School Leaving Certificate & Marksheet
– Bachelor’s Degree & Transcript
– English Language Qualification (see Entry Requirements)
– CV & Personal Statement
– 2 Reference Letters
– ID/Passport
Payment of €50 application fee (non-refundable) for the Admissions Department to officially evaluate your application and if successful to receive your Offer for a Place to Study at UCLan Cyprus.
APPLY NOW * International Applicants: once you receive your Offer Letter, you will proceed to the Visa Application Steps. Find more information here.