Curriculum Overview: Data Privacy and Governance
Data Privacy and Governance
Curriculum Overview: Data Privacy and Governance
This curriculum provides a comprehensive roadmap for mastering data security, privacy, and governance within the AWS ecosystem, specifically aligned with the AWS Certified Data Engineer - Associate (DEA-C01) requirements. It covers the end-to-end protection of data assets, from network-level security to fine-grained access control and regulatory compliance.
Prerequisites
To successfully engage with this curriculum, learners should possess the following foundational knowledge and experience:
- Experience: 1–2 years of hands-on experience with core AWS services (S3, IAM, VPC).
- Data Engineering Fundamentals: Understanding of ETL/ELT pipelines, data lake architectures, and the effects of data volume/velocity on security.
- Identity Basics: Familiarity with the Shared Responsibility Model and basic Identity and Access Management (IAM) concepts.
- Networking: Basic understanding of VPCs, subnets, and security groups.
- Programming: Language-agnostic understanding of scripting (Python or SQL) for automating security tasks.
Module Breakdown
| Module ID | Module Title | Primary AWS Services | Difficulty |
|---|---|---|---|
| DPG-01 | Network & Infrastructure Security | VPC, Security Groups, PrivateLink | Moderate |
| DPG-02 | Identity & Authentication | IAM, Secrets Manager, SageMaker | Moderate |
| DPG-03 | Authorization & Access Control | Lake Formation, Redshift, IAM Policies | High |
| DPG-04 | Data Protection (Encryption/Masking) | KMS, Macie, S3, Glue | High |
| DPG-05 | Governance, Quality & Auditing | CloudTrail, CloudWatch, DataBrew, Glue | Moderate |
Learning Objectives per Module
DPG-01: Network & Infrastructure Security
- Objective: Secure data analytics workloads at the network layer.
- Key Outcomes: Update VPC security groups to restrict traffic and implement VPC Endpoints to keep data traffic within the AWS backbone.
DPG-02: Identity & Authentication
- Objective: Manage identities and credentials for users and services.
- Key Outcomes: Create/rotate credentials using AWS Secrets Manager and configure IAM roles for service-to-service communication (e.g., Lambda accessing S3).
DPG-03: Authorization & Access Control
- Objective: Implement fine-grained access control across data stores.
- Key Outcomes: Use AWS Lake Formation to manage row, column, and cell-level permissions for Athena and Redshift. Construct custom IAM policies that adhere to the Principle of Least Privilege.
DPG-04: Data Protection
- Objective: Ensure data confidentiality and integrity.
- Key Outcomes: Configure Server-Side Encryption (SSE) using AWS KMS and implement PII (Personally Identifiable Information) discovery using Amazon Macie.
[!IMPORTANT] Data Masking is often a requirement for compliance (GDPR/HIPAA). You must be able to anonymize sensitive data before it reaches downstream consumers or non-production environments.
DPG-05: Governance, Quality & Auditing
- Objective: Maintain data health and auditability.
- Key Outcomes: Centralize API activity logs using AWS CloudTrail Lake and implement data quality rules using DQDL (Data Quality Definition Language) in Glue.
Success Metrics
Learners can measure their mastery of the curriculum through the following performance indicators:
- Least Privilege Implementation: Ability to write a custom IAM policy that grants access to specific S3 prefixes and KMS keys without using wildcard (
*) permissions for actions. - Encryption Proficiency: Successfully demonstrating cross-account data sharing where the destination account can decrypt objects using a CMK (Customer Managed Key).
- Audit Readiness: The ability to query CloudTrail logs via Athena to identify the specific IAM user who deleted a critical S3 object.
- Governance Automation: Setting up an S3 Lifecycle Policy to automatically transition data to Glacier and expire it after a legal retention period (e.g., 7 years).
Real-World Application
In a professional setting, the skills gained from this curriculum translate to the following critical tasks:
- Regulatory Compliance: Aligning enterprise data lakes with GDPR or HIPAA by ensuring data residency (sovereignty) and PII masking.
- Multi-Tenant Architectures: Building secure data sharing patterns between different business units or external partners using Redshift Data Sharing without moving or copying data.
- Secure Pipelines: Automating the rotation of database credentials so that no human or application code ever has hardcoded passwords.
[!TIP] Always use AWS Config to track configuration changes in your account. It provides a historical record of resource changes, which is invaluable for security audits and troubleshooting pipeline failures.