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A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A data engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A data engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.
| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified Professional Data Engineer Exam |
| Exam Number: | Professional Data Engineer |
| Related Certifications: | Google Cloud Certified - Associate Cloud Engineer Google Cloud Certified - Professional Machine Learning Engineer Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Professional Data Analytics Engineer |
| Exam Duration: | 120 minutes |
| Passing Score: | Not publicly disclosed (scaled scoring system) |
| Available Languages: | Spanish, Japanese, German, French, Portuguese, English |
| Certificate Validity Period: | 2 years |
| Exam Format: | multiple choice, case study, multiple select |
| Real Exam Qty: | Approximately 50–60 multiple choice and multiple select questions |
| Exam Price: | $200 USD |
| Recommended Training: | Google Cloud Professional Data Engineer Course (Coursera) Google Cloud Data Engineering Learning Path |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Data-Engineer日本語 Sample Questions |
| Exam Way: | Online proctored exam or onsite test center (Kryterion Webassessor) |
| Pre Condition: | No formal prerequisites required; recommended experience with data processing and Google Cloud Platform services |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
The Google Professional Data Engineer Certification is one of the highest level of certification mainly focussing to the professional Data Engineering.
There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google professional Data Engineer.
You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path
Reference: https://cloud.google.com/certification/data-engineer
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.
| Section | Weight | Objectives |
|---|---|---|
| Building and operationalizing data processing systems | 24% | - Data ingestion and integration
|
| Operationalizing machine learning models | 26% | - Model deployment and monitoring
|
| Ensuring solution quality | 28% | - Security and governance
|
| Designing data processing systems | 22% | - Batch and streaming data processing design
|
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