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Professional Data Engineer Exam Details

Like other Google exams, this exam also consists of multiple choice and multiple select questions. Consider the fact that you need to pay $200 for the registration. After that, you will access the test for 2 hours which is presented either in English or Japanese. Moreover, you can either take the exam online or have to find a test center near your place to take this test.

There is no formal prerequisite for the exam but it is recommended to have 3-4 years of experience within the data engineering field and to be responsible for the tasks related to data engineering and machine learning. So, on the final test day, you need to have exhaustive knowledge about these domains to perform your best.

• Providing solution quality
• Building data processing systems
• Operationalizing machine learning models
• Designing data processing systems

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Who should take the Google Professional Data Engineer exam

Individuals should pursue the exam if they want to demonstrate their expertise and ability to design and develop Data Engineering. Following professional get benefited from Google Professional Data Engineer Certification

• Business analysts
• Data architects
• Data scientists
• Developers responsible for managing big data transformation initiatives
• Data analysts
• Data engineers

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

The following will be discussed here:

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

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DOWNLOAD DEMO

This course is normally taken by data scientists, data analysts, and business analysts who are in the field of Google Сloud. It is a good way to prepare for your final exam because it teaches you all the details including 7 modules that cover all the Professional Data Engineer exam objectives:

• Scaling Data Analytics
• Introducing Google Cloud Platform ‘
• Data Analytics on the Cloud
• Additional Resources
• Machine Learning
• Data Processing Architectures
• Compute and Storage Fundamentals

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