10 Principles of Data Governance According To Rob Brennan
What do you think? https://www.perplexity.ai/page/rob-brennan-data-governance-ex-_A6D5187QSuZSGj1jG1w7A#f75fd228-7953-4580-80ad-9edf638ca383 Dr. Rob Brennan's research and expertise, the core principles of data governance encompass several key areas: 1. Data Quality Management: This is a fundamental aspect of data governance, focusing on ensuring the accuracy, completeness, and reliability of data. Brennan emphasizes the importance of maintaining high-quality data throughout its lifecycle[1][2]. 2. Data Privacy and Security: Protecting sensitive information and ensuring compliance with data protection regulations is a critical principle. Brennan's work highlights the need for robust security measures and privacy-preserving techniques in data governance frameworks[1][3]. 3. Regulatory Compliance: Adhering to relevant laws and regulations is a core principle of data governance. Brennan's research addresses the challenges of maintaining compliance in various sectors, including healthcare[1][4]. 4. Data Value and Risk Management: Brennan's work emphasizes the importance of understanding and maximizing the value of data while managing associated risks. This includes developing methodologies for data valuation and risk assessment[3][5]. 5. AI Governance: As an emerging area of focus, Brennan incorporates AI governance into data governance principles, addressing the ethical and practical challenges of managing AI systems and their data[1][6]. 6. Knowledge Graphs: Brennan's research highlights the use of knowledge graphs as a tool for enhancing data governance, particularly in organizing and linking complex data structures[3][6]. 7. Transparency and Accountability: Establishing clear roles, responsibilities, and processes for data management is a key principle in Brennan's approach to data governance[2][3]. 8. Interoperability and Standards: Brennan's work, including his contributions to international standards, underscores the importance of interoperability and standardization in effective data governance[3][7].