Understanding functional and technical aspects of Google Professional Data Engineer Exam Ensuring solution quality

The following will be discussed here:

• Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
• Pipeline monitoring (e.g., Stackdriver)
• Ensuring scalability and efficiency
• Designing for security and compliance
• Verification and monitoring
• Assessing, troubleshooting, and improving data representations and data processing infrastructure
• Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
• Designing for data and application portability (e.g., multi-cloud, data residency requirements)
• Ensuring flexibility and portability
• Mapping to current and future business requirements
• Performing data preparation and quality control (e.g., Cloud Dataprep)
• Building and running test suites
• Choosing between ACID, idempotent, eventually consistent requirements
• Resizing and autoscaling resources
• Identity and access management (e.g.,Cloud IAM)
• Ensuring reliability and fidelity
• Ensuring privacy (e.g., Data Loss Prevention API)
• Data staging, cataloging, and discovery
• Data security (encryption, key management)

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Ensuring Solution Quality

The last section of the certification exam evaluates the ability of the learners to design for security & compliance, including identity & access management, legal compliance, data security, and privacy ensuring. Moreover, they should be able to ensure flexibility & portability, reliability & fidelity, as well as scalability & efficiency.

Reference: https://cloud.google.com/certification/data-engineer

Who is the Professional Data Engineer Exam Intended for?

This exam is designed for individuals who are experts in designing, building, securing, and monitoring data processing systems with a particular emphasis on compliance and security. The candidate who wants to take the Professional Data Engineer exam should have the ability to deploy, leverage, and training pre-existing machine learning models. Moreover, every applicant should have experience of more than 3 years including 1-year experience in designing and handling solutions utilizing GCP.