Module #1 Introduction to Data Lakes Overview of data lakes, their benefits, and importance of security and privacy
Module #2 Data Security Fundamentals Basic security concepts, threat models, and security principles
Module #3 Data Privacy Fundamentals Introduction to data privacy, regulations, and compliance
Module #4 Data Lake Architecture Overview of data lake architecture, components, and security challenges
Module #5 Data Ingestion and Security Security considerations for data ingestion, including data validation and encryption
Module #6 Storage Security Security measures for data storage, including access controls and encryption
Module #7 Data Catalog and Metadata Security Securing data catalogs and metadata, including access controls and encryption
Module #8 Data Processing and Security Security considerations for data processing, including data transformation and analytics
Module #9 Data Access Control Implementing access controls for data lakes, including role-based access control and attribute-based access control
Module #10 Data Encryption and Masking Techniques for encrypting and masking sensitive data in data lakes
Module #11 Identity and Access Management IAM concepts and implementations for data lakes, including authentication and authorization
Module #12 Network Security for Data Lakes Securing data lakes from network-based threats, including firewalls and VPNs
Module #13 Compliance and Regulatory Requirements Overview of regulatory requirements for data lakes, including GDPR, HIPAA, and CCPA
Module #14 Data Loss Prevention (DLP) Implementing DLP strategies for data lakes, including anomaly detection and incident response
Module #15 Incident Response and Disaster Recovery Responding to security incidents and developing disaster recovery plans for data lakes
Module #16 Monitoring and Auditing Implementing monitoring and auditing for data lakes, including log analysis and security information event management (SIEM)
Module #17 Case Studies in Data Lake Security Real-world examples of data lake security implementations and breaches
Module #18 Security Best Practices for Data Lakes Industry-recognized security best practices for data lakes
Module #19 Privacy by Design Implementing privacy by design principles for data lakes
Module #20 Anonymous Data and K-Anonymity Techniques for anonymizing data in data lakes, including k-anonymity
Module #21 Differential Privacy Implementing differential privacy for data lakes, including noise addition and aggregation
Module #22 Privacy-Preserving Data Analysis Techniques for analyzing sensitive data in data lakes while preserving privacy
Module #23 Data Lake Security Governance Developing governance models for data lake security, including policies and procedures
Module #24 Security Assessment and Testing Assessing and testing data lake security, including vulnerability scanning and penetration testing
Module #25 Course Wrap-Up & Conclusion Planning next steps in Data Security and Privacy in Data Lakes career
