PDF Version DemoGoogle Professional Data Engineer Practice Test Questions, Google Professional Data Engineer Exam Practice Test Questions
The Google Professional Data Engineer certification is designed to evaluate the candidates’ skills in designing data processing systems and ensuring solution quality. It is also created to measure their competence in building and operationalizing data processing systems and operationalizing ML models. The potential applicants must complete a single exam to get certified.
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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Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and operationalizing data processing systems | 25% | - Deploying and managing systems
|
| Topic 2: Maintaining and automating data workloads | 18% | - Resource optimization
|
| Topic 3: Operationalizing machine learning models | 20% | - Preparing data for ML
|
| Topic 4: Designing data processing systems | 20% | - Designing for regulatory and security requirements
|
| Topic 5: Ensuring solution quality and reliability | 17% | - Troubleshooting and optimization
|
