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Exam Topics

The syllabus of the Google Professional Data Engineer exam is divided into 4 topics, each covering specific knowledge and skills that the candidates need to develop while preparing for the test. A full outline of the exam content can be viewed on the official website. The highlights of the domains covered in the test are as follows:

Topic 1. Designing Data Processing Systems

To answer the questions related to this first topic of the certification exam, the individuals need to demonstrate their proficiency in selecting the proper storage technologies. This includes their understanding of data modeling, schema design, distributed systems, as well as tradeoffs involving throughput, latency, and transactions. Moreover, the applicants need to have the ability to map storage systems to the business needs. It also measures one’s skills in designing data pipelines, designing a data processing solution, as well as migrating data warehousing & data processing.

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

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

The following will be discussed here:

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