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Professional-Data-Engineer Dumps - Google Professional Data Engineer Exam Practice Exam Questions

Google Professional-Data-Engineer - Google Cloud Certified Practice Exam

  • Certification Provider:Google
  • Exam Code:Professional-Data-Engineer
  • Exam Name:Google Professional Data Engineer Exam Exam
  • Total Questions:372 Questions and Answers
  • Updated on:Nov 22, 2024
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Google Professional-Data-Engineer This Week Result

Professional-Data-Engineer Question and Answers

Question # 1

What are the minimum permissions needed for a service account used with Google Dataproc?

Options:

A.  

Execute to Google Cloud Storage; write to Google Cloud Logging

B.  

Write to Google Cloud Storage; read to Google Cloud Logging

C.  

Execute to Google Cloud Storage; execute to Google Cloud Logging

D.  

Read and write to Google Cloud Storage; write to Google Cloud Logging

Discussion 0
Question # 2

When a Cloud Bigtable node fails, ____ is lost.

Options:

A.  

all data

B.  

no data

C.  

the last transaction

D.  

the time dimension

Discussion 0
Question # 3

Which role must be assigned to a service account used by the virtual machines in a Dataproc cluster so they can execute jobs?

Options:

A.  

Dataproc Worker

B.  

Dataproc Viewer

C.  

Dataproc Runner

D.  

Dataproc Editor

Discussion 0

PDF vs Software Version

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Professional-Data-Engineer FAQs

The role of a Professional Data Engineer in Google Cloud involves designing, building, and maintaining data processing systems that are scalable, efficient, and reliable. They work with large datasets to extract insights, drive business decisions, and optimize data-driven processes.

A Professional Data Engineer makes data usable and valuable for others by designing data processing pipelines that transform raw data into meaningful insights. They ensure data quality, implement data governance practices, and create intuitive interfaces for accessing and analyzing data.

The key responsibilities of a Professional Data Engineer in data processing include designing and implementing data pipelines, integrating data from various sources, cleaning and transforming data, optimizing data storage and retrieval, and ensuring data security and compliance.

The exam assesses the ability to design data processing systems by testing candidates on their understanding of data processing concepts, their knowledge of Google Cloud Platform (GCP) data processing services, their proficiency in designing scalable and efficient data pipelines, and their ability to optimize data processing workflows for performance and cost efficiency.

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