Welcome to the final module of our Data Engineering course, where we focus on the critical aspects of security and privacy in data engineering. In this module, we will explore key concepts and techniques that data engineers must master to protect sensitive data and comply with privacy regulations.
What You’ll Learn:
1) Data Privacy Fundamentals: Understand the importance of data privacy and how it impacts data engineering. Learn about key regulations like the GDPR and CCPA that dictate how personal data should be handled, stored, and protected.
2) Data Masking: Discover how data masking protects sensitive information by replacing it with fictional data, ensuring the privacy of personal information while keeping data usable for testing and analysis.
3) Data Minimization: Learn the principle of collecting, storing, and processing only the minimum amount of personal data necessary, reducing risks and ensuring compliance with legal requirements.
4) Anonymization & Pseudonymization: Explore techniques that protect personal information by making data either irreversibly unidentifiable (anonymization) or reversible through pseudonyms (pseudonymization).
5) Data Encryption: Dive into data encryption, a crucial method for converting sensitive information into an unreadable format, ensuring that data remains secure even if intercepted or accessed without authorization.
6) Access Controls: Understand the importance of access controls in regulating who can view or use data. Implementing these controls is essential for preventing data breaches and maintaining data integrity and confidentiality.
Join us as we cover these essential security and privacy techniques, equipping you with the knowledge and skills to protect sensitive data in any data environment.
Негізгі бет Data Privacy Concepts for Data Engineers | Enterprise Big Data Engineer
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