Auditing is vital for a strong data governance framework, helping organisations ensure compliance, manage risks, and maintain accountability. It validates data governance policies, identifies process gaps, and promotes transparency. Key audit components include access logs, data quality checks, and compliance metrics. Overall, auditing enhances long-term data integrity and organisational confidence.
Category: Data Management
The Ultimate Guide to Balancing Data Security and Accessibility
In today's data-driven environment, organisations must balance data security and accessibility to meet business needs and compliance. This involves understanding data sensitivity, implementing role-based access, using encryption, monitoring user activity, automating access management, creating a data security policy, and regularly reviewing access rights. A proactive approach ensures sensitive information is protected while maintaining necessary accessibility.
Access-Based Controls: Ensuring Secure and Auditable Data Usage
Access-based controls (ABC) are essential for data security, regulating who accesses data and what actions they can take. Key components include Role-Based Access Control and the Least Privilege Principle. Best practices emphasise automation, segmentation, staff training, and monitoring to ensure robust data governance while maintaining accountability and compliance across organisations.
High-Level Architecture Diagrams: Visualising Your Data Ecosystem
High-level architecture diagrams offer crucial insights into data flow and connectivity within organisations. They enhance clarity, facilitate collaboration, and promote scalability. Adopting standards like BPMN can streamline processes, while tools such as Microsoft Visio aid in creating these diagrams. Regular updates ensure accuracy, supporting effective data governance strategies.
How Should We Classify Data – A Quick Introduction to Data Classification
This post emphasises the importance of data classification within Data Governance, highlighting four potential classification levels: Public, Internal, Confidential, and Restricted. It stresses contextualising classification based on industry standards, steps to classify data, and the necessity of inventorying assets. Automation tools like Microsoft Purview facilitate consistent data management throughout its lifecycle.