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Introduction to Data Security and Privacy Engineering

Fundamentals of Data Security

Identifying Sensitive Data in Modern Platforms

Technical Controls: Data Encryption

Introduction to Data Encryption

Encryption at Rest and in Transit

Technical Controls: Data Masking

Defining Data Masking and Obfuscation

Dynamic vs. Static Data Masking

Technical Controls: Row-Level Security (RLS)

Understanding Row-Level Security

Implementing Row-Level Security Concepts

Quizzes

Quiz: Fundamentals of Data Security

Quiz: Encryption Controls

Quiz: Data Masking

Quiz: Row-Level Security

Quiz: Comprehensive Security Controls

Course Wrap-Up and Feedback

Course Evaluation Survey

In today's data-driven world, safeguarding sensitive information is no longer just a compliance requirement—it is a critical business imperative. Welcome to "Data Security and Privacy Engineering for Modern Platforms," a comprehensive course designed to equip you with the essential skills needed to protect user data across modern data architectures.

In today's data-driven world, safeguarding sensitive information is no longer just a compliance requirement—it is a critical business imperative. Welcome to "Data Security and Privacy Engineering for Modern Platforms," a comprehensive course designed to equip you with the essential skills needed to protect user data across modern data architectures. Whether you are working with cloud data warehouses, data lakes, or complex data pipelines, this course provides a deep dive into the foundational principles of data security, including the CIA triad (Confidentiality, Integrity, and Availability) and the evolving role of the privacy engineer.

Throughout this course, you will explore how to identify and classify sensitive data such as Personally Identifiable Information (PII) and Protected Health Information (PHI), while navigating regulatory frameworks like GDPR and CCPA. We will guide you through the implementation of robust technical controls, starting with data encryption at rest and in transit using industry-standard protocols and Key Management Systems (KMS). You will also master advanced techniques like Static and Dynamic Data Masking (SDM/DDM) to obfuscate data for non-production environments and real-time querying. Finally, you will learn how to implement Row-Level Security (RLS) to restrict unauthorized access at a granular level, culminating in a defense-in-depth strategy. By the end of this course, you will have the practical knowledge to architect secure, compliant, and resilient data platforms.

Data Security and Privacy Engineering for Modern Platforms

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            <p>The rapid expansion of modern data platforms, including cloud data warehouses and data lakes, has fundamentally transformed how organizations store and process information. Consequently, safeguarding sensitive records such as Personally Identifiable Information (PII) and Protected Health Information (PHI) has become a critical imperative. Driven by stringent regulatory frameworks like the GDPR and CCPA, organizations must adopt rigorous data protection controls to maintain compliance and trust. This course provides a comprehensive examination of data security and privacy engineering, establishing a foundational understanding of the confidentiality, integrity, and availability (CIA) triad. It further explores the essential role of privacy engineers in executing data discovery processes and securing data pipelines against unauthorized access.</p>

<p>To effectively mitigate risks and ensure regulatory compliance, privacy professionals must implement a robust, defense-in-depth security strategy utilizing advanced technical controls. Throughout this curriculum, learners will explore the mechanics and application of data encryption, distinguishing between data at rest and in transit while examining the function of cryptographic keys and key management systems (KMS). Furthermore, the course delves into data masking and obfuscation techniques, comparing static and dynamic masking methodologies used to protect sensitive information in real-time without compromising utility. Finally, the implementation of Row-Level Security (RLS) will be analyzed in detail, demonstrating how organizations can restrict unauthorized access to specific data records based on user permissions and roles, thereby ensuring a highly secure and resilient data architecture.</p>
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