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Google Professional-Data-Engineer Exam Overview:
| Certification Vendor: | Google Cloud |
| Exam Name: | Google Cloud Certified Professional Data Engineer |
| Exam Number: | Professional-Data-Engineer |
| Exam Price: | $200 USD |
| Real Exam Qty: | 50-60 |
| Passing Score: | Not officially published (estimated ~80%) |
| Available Languages: | English, Japanese |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple-choice, Multiple-select |
| Related Certifications: | Google Cloud Certified Professional Data Engineer |
| Certificate Validity Period: | 2 years |
| Sample Questions: | Google Professional-Data-Engineer Sample Questions |
| Exam Way: | Online (remote proctored) or at a testing center (Kryterion) |
| Pre Condition: | No mandatory prerequisites. Recommended: 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud. |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
What is the duration, language, and format of Google Professional Data Engineer Exam
- Format: Multiple choices, multiple answers
- Length of Examination: 120 minutes
- Passing score: 80%
- Cost: $200
- Number of Questions: 50-60
- Language: English (U.S.), Japanese, Spanish, and Portuguese
Reference: https://cloud.google.com/certification/data-engineer
To pass the Google Professional-Data-Engineer exam, candidates must have a solid understanding of data engineering concepts and techniques, as well as practical experience working with the Google Cloud Platform. They must be able to design and implement data processing systems that are secure, scalable, and efficient, and have the ability to troubleshoot and optimize these systems as needed. Professional-Data-Engineer exam is challenging and comprehensive, but passing it can open up many career opportunities in data engineering, especially for those interested in working with Google Cloud Platform.
Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Maintaining and automating data workloads (~15% of the exam) | 15% | - Designing for reliability and fidelity
|
| Ingesting and processing the data (~20% of the exam) | 20% | - Building and maintaining data structures and databases
|
| Storing the data (~20% of the exam) | 20% | - Planning for using a data warehouse
|
| Designing data processing systems (~30% of the exam) | 30% | - Designing data pipelines
|
| Preparing and using data for analysis (~15% of the exam) | 15% | - Sharing data securely
|
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