Navigate regulatory compliance and ethical data practices
Learn to manage data responsibly, ensuring legal adherence and ethical integrity in business operations.
This module covers key aspects of managing data within legal and ethical boundaries. Students will learn to evaluate different frameworks for acquiring, storing, and transforming data. They will understand the legal and ethical issues involved in data management and develop strategies for handling business data responsibly.
The course also explores the role of artificial intelligence in data analysis, ensuring students grasp both the technical and legal aspects. This module prepares students for responsible leadership in the digital business world by emphasising ethical and societal impacts.
Innovative online learning with future-facing approaches
This fully online module uses innovative teaching methods, combining hybrid learning with expert tutorship. Students engage in synchronous lectures, asynchronous study, and lab activities. Key strategies include problem-based learning, gamification, and flipped classroom approaches.
Emerging technologies, such as artificial intelligence, enhance the digital learning experience. These methods ensure a dynamic and interactive environment, promoting deep understanding and practical skills. The course culminates in a proctored written test and a final exam, each accounting for 50% of the grade, ensuring comprehensive mastery of the material.
Assessments are ongoing and final, including exams, assignments, and projects. A significant project (50%) applies cybersecurity to real business problems, while a final test (50%) ensures a comprehensive understanding of the material.
Time commitment
Classroom and demonstrations: 24 hours
Practical work/tutorials: 24 hours
Independent learning: 77 hours
Total: 125 hours
Credit points
5 ECTS
Full course breakdown
Subjects covered:
Data Governance and Ethics is a 5 ECTS module delivered over 4 hours per week for 12 weeks. An indicative schedule of topics to be addressed each week is outlined below:
- Introduction to Data Governance (DG)
- Overview of data governance
- Importance and objectives of data governance in contemporary organisations
- Big Data Management Principles
- Data lifecycle management
- Principles of data quality, data provenance and data generation
- Understanding master data and its importance
- Methods for assessing and improving data quality
- Data Integrity and Security
- Techniques and practices for ensuring data integrity
- Data security challenges and strategies
- Implementing master data management and data quality processes
- DG Frameworks
- Examining policies, principles, rules, and procedures
- Different operating models
- Implementation challenges and best practices
- Data Architecture and Metadata Management
- Designing data architecture tailored to enterprise needs
- Using metadata to enhance data governance and usage
- Integrating metadata management tools into enterprise IT infrastructure
- Data Risk Management
- Understanding data-related risks
- Roles, responsibilities, and maturity levels in risk management
- Assessing risks related to data
- Managing risks related to data confidentiality and security
- Ensuring regulatory compliance with data
- Implementing Data Governance for Business Value Creation
- Aligning data governance with business strategy
- Identifying stakeholders and responsibilities
- Developing data governance policies and standards
- Utilizing data for predictive analysis and decision-making
- Use cases of data analytics to enhance business processes
- Strategies for monetizing data and creating new business models
- Ethical Concepts and Frameworks
- Introduction to ethics in data management
- Ethical principles, standards, and practice
- Privacy, Analytics, and Ethics
- Balancing analytics ambitions with privacy laws and ethical standards
- Case studies
- Ethics and AI
- Ethical considerations in AI and ML
- Mitigating biases and ensuring fairness
- Governance of AI and Advanced Analytics
- Emerging trends and challenges in AI governance
- Regulatory and ethical frameworks for AI
- Business Data Ethics and Future Trends
- Applying ethical principles in business data analytics
- Future trends in data governance and ethics
Shaping tomorrow’s digital leaders with Digital4Business
This module is included in the EU-funded Digital4Business programme, an online master’s aimed at cultivating future digital leaders. Discover how digital transformation fuels business innovation and efficiency, providing you with the crucial skills to excel and lead in the fast-changing digital landscape.
FAQ
Minimum C1 English proficiency, plus 2 years' work or education in an English-speaking environment. IELTS: 6.0; TOEFL PBT: 600; TOEFL CBT: 200; TOEFL iBT: 100
Applicants need a suitable cognate EQF Level 6 qualification (e.g. STEM, economics, etc.). Description of the eight EQF levels Those without such a qualification will undergo an interview and assessment to determine the suitability of their certifications, other qualifications, and/or professional experience.
This EU-funded programme is open to all EU nationals with a passport or valid ID from one of the 27 EU countries