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1. Implementing GDPR Compliance in an Azure Data Engineering Project Implementing GDPR Compliance in an Azure Data Engineering Project Introduction Introduction The General Data Protection Regulation (GDPR) General Data Protection Regulation (GDPR) is a key regulation designed to protect personal data and the privacy of individuals within the European Union (EU) (EU). Organizations handling EU citizens' data must comply with GDPR by ensuring data security, transparency, and accountability data security, transparency, and accountability. In an Azure Data Engineering Engineering project, compliance requires strategic implementation of security, governance, and auditing measures governance, and auditing measures. This document outlines key steps to achieve GDPR compliance GDPR compliance in Azure-based data solutions. European Union Azure Data security, Key GDPR Principles Key GDPR Principles Organizations must adhere to the following GDPR principles: Principle Principle Description Description Lawfulness, Fairness, and Lawfulness, Fairness, and Transparency Transparency Collect and process personal data legally and transparently. Use data only for specified and legitimate purposes. Purpose Limitation Purpose Limitation Data Minimization Data Minimization Collect only the necessary amount of data.

2. Accuracy Accuracy Ensure stored data is accurate and up-to-date. Storage Limitation Storage Limitation Retain data only as long as necessary. Secure personal data against unauthorized access and processing. Maintain detailed records to demonstrate compliance. Integrity and Confidentiality Integrity and Confidentiality Accountability Accountability Implementing GDPR Compliance in Azure Data Engineering Implementing GDPR Compliance in Azure Data Engineering 1. Data Discovery and Classification 1. Data Discovery and Classification The first step is identifying and classifying personal data across Azure services Azure services. Azure Purview Azure Purview helps with: Scanning structured and unstructured data sources. Identifying personally identifiable information (PII Tagging data with sensitivity labels sensitivity labels. PII). Diagram: Data Discovery & Classification Flow Diagram: Data Discovery & Classification Flow (Placeholder for a flowchart showing Azure Purview’s role in data classification.) 2. Secure Data Storage and Encryption 2. Secure Data Storage and Encryption GDPR mandates secure storage multiple encryption mechanisms: secure storage and processing processing of personal data. Azure offers Security Measure Security Measure Data Encryption at Rest Data Encryption at Rest Data Encryption in Transit Data Encryption in Transit TLS Encryption Key Management Key Management Azure Service Azure Service Azure Storage Service Encryption (SSE) Azure Key Vault 3. Data Access Control and Identity Management 3. Data Access Control and Identity Management To restrict unauthorized access restrict unauthorized access, use: Azure Active Directory (AAD) Azure Active Directory (AAD) for Role Privileged Identity Management (PIM) Privileged Identity Management (PIM) to manage privileged access. Multi Multi- -Factor Authentication (MFA) Factor Authentication (MFA) for identity verification. Managed Identities Managed Identities for secure access without exposing credentials. Role- -Based Access Control (RBAC) Based Access Control (RBAC).

3. 4. Anonymization and Data Ma 4. Anonymization and Data Masking sking Techniques to minimize risk: Dynamic Data Masking Dynamic Data Masking in Azure SQL Database Row Row- -Level Security (RLS) Level Security (RLS) in Azure Synapse Analytics Azure Data Factory Azure Data Factory for pseudonymization pseudonymization. Azure SQL Database. Azure Synapse Analytics. 5. Data Retention and Right to Be Forgotten 5. Data Retention and Right to Be Forgotten GDPR requires personal data to be retained only as necessary individuals to request data deletion data deletion. retained only as necessary and allows Requirement Requirement Automated Data Retention & Deletion Automated Data Retention & Deletion Azure Blob Storage lifecycle policies Azure Service Azure Service Track Data Changes & Deletions Track Data Changes & Deletions Azure SQL Database Temporal Tables Automate De Automate Deletion Requests letion Requests Azure Logic Apps 6. Audit Logs and Monitoring 6. Audit Logs and Monitoring Maintaining logs is essential for compliance essential for compliance. Enable Azure Monitor & Log Analytics Enable Azure Monitor & Log Analytics for real Use Azure Security Center Use Azure Security Center for threat detection Implement Azure Sentinel Implement Azure Sentinel for advanced security analytics real- -time tracking time tracking. threat detection. advanced security analytics. 7. Data Breach Notification and Incident Management 7. Data Breach Notification and Incident Management GDPR mandates breach notifications breach notifications within 72 hours 72 hours. Automated breach response: Automated breach response: Azure Security Center Alerts Azure Security Center Alerts for threat detection. Azure Sentinel Azure Sentinel for automated incident respons automated incident response e. Azure Logic Apps Azure Logic Apps to automate notification processes notification processes. Conclusion Conclusion Ensuring GDPR compliance GDPR compliance in an Azure Data Engineering combination of data governance, security controls, access management, and data governance, security controls, access management, and Azure Data Engineering project requires a

4. monitoring monitoring. By leveraging Azure’s built-in security and compliance tools, organizations can efficiently meet GDPR requirements while ensuring robust data protection data protection. robust For More Information about For More Information about Azure Data Engineer Online Training Contact Call/WhatsApp: Contact Call/WhatsApp: +91 7032290546 Visit: Visit: https://www.visualpath.in/online-azure-data-engineer-course.html