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Understanding functional and technical aspects of Google Professional Data Engineer Exam Ensuring solution quality
The following will be discussed here:
- Performing data preparation and quality control (e.g., Cloud Dataprep)
- Verification and monitoring
- Assessing, troubleshooting, and improving data representations and data processing infrastructure
- Building and running test suites
- Ensuring scalability and efficiency
- Designing for data and application portability (e.g., multi-cloud, data residency requirements)
- Pipeline monitoring (e.g., Stackdriver)
- Data security (encryption, key management)
- Ensuring flexibility and portability
- Ensuring reliability and fidelity
- Choosing between ACID, idempotent, eventually consistent requirements
- Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
- Ensuring privacy (e.g., Data Loss Prevention API)
- Identity and access management (e.g.,Cloud IAM)
- Data staging, cataloging, and discovery
- Resizing and autoscaling resources
- Designing for security and compliance
- Mapping to current and future business requirements
- Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
Google Professional Data Engineer Certified Professional salary
The average salary of a Google Professional Data Engineer Certified Expert in
- England - 115,632 POUND
- United State - 151,247 USD
- India - 25,42,327 INR
- Europe - 135,347 EURO
The Google Professional Data Engineer certification is designed to equip the individuals with the required knowledge and skills to enable data-driven decision-making through collecting, transforming, and publishing data. To earn this certificate, the candidates will be required to pass a single test measuring their skills in leveraging, deploying, and continuously training pre-existing machine learning models. The qualifying exam also evaluates the ability of the applicants to design, build, operationalize, monitor, and secure data processing systems.
Reference: https://cloud.google.com/certification/data-engineer
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