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Professional-Data-Engineer Exam Dumps : Google Professional Data Engineer Exam

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Google Professional-Data-Engineer Exam Dumps FAQs

Q. # 1: What is the Google Professional-Data-Engineer Exam?

The Google Professional-Data-Engineer certification validates your ability to design, build, operationalize, secure, and monitor data processing systems on Google Cloud.

Q. # 2: Who should take the Google Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is targeted at data engineers, data analysts, machine learning engineers, and cloud architects who want to demonstrate their expertise in managing data solutions on Google Cloud Platform.

Q. # 3: What topics are covered in the Google Professional-Data-Engineer Exam?

The exam covers:

  • Designing data processing systems

  • Building and operationalizing data pipelines

  • Managing data solutions

  • Ensuring solution quality

  • Leveraging machine learning models

Q. # 4: What is the format of the Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is multiple-choice and multiple-select, delivered online or at a testing center via Kryterion.

Q. # 5: Are there any prerequisites for the Professional-Data-Engineer Exam?

There are no formal prerequisites, but Google recommends 3+ years of industry experience, including 1+ year with Google Cloud.

Q. # 6: What is the difference between Google Professional-Data-Engineer and Associate-Cloud-Engineer Exam?

The Google Professional Data Engineer and Associate Cloud Engineer exams differ mainly in focus, difficulty level, and job roles.

  • The Associate Cloud Engineer certification is entry-level, designed for professionals who deploy, manage, and maintain applications on Google Cloud Platform (GCP). It validates general cloud operations, setup, and configuration skills.
  • The Professional Data Engineer, on the other hand, is an advanced-level certification focused on designing, building, and managing data processing systems, data analytics, and machine learning models using GCP services like BigQuery, Dataflow, Dataproc, and Pub/Sub.

Q. # 7: What is the difficulty level of the Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is considered moderate to advanced, requiring hands-on experience with GCP data services and machine learning workflows.

Q. # 8: Where can I find Google Professional-Data-Engineer exam dumps and practice tests?

Visit CertsTopics for verified Professional-Data-Engineer exam dumps, questions and answers, and practice tests that mirror the real exam and come with a success guarantee.

Q. # 9: Is there a success guarantee with CertsTopics materials?

Yes, CertsTopics provides a success guarantee with regularly updated Professional-Data-Engineer dumps material crafted by certified professionals to help you pass on your first attempt.

Google Professional Data Engineer Exam Questions and Answers

Question 1

Your company has recently grown rapidly and now ingesting data at a significantly higher rate than it was previously. You manage the daily batch MapReduce analytics jobs in Apache Hadoop. However, the recent increase in data has meant the batch jobs are falling behind. You were asked to recommend ways the development team could increase the responsiveness of the analytics without increasing costs. What should you recommend they do?

Options:

A.

Rewrite the job in Pig.

B.

Rewrite the job in Apache Spark.

C.

Increase the size of the Hadoop cluster.

D.

Decrease the size of the Hadoop cluster but also rewrite the job in Hive.

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Question 2

Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?

Options:

A.

Use Google Stackdriver Audit Logs to review data access.

B.

Get the identity and access management IIAM) policy of each table

C.

Use Stackdriver Monitoring to see the usage of BigQuery query slots.

D.

Use the Google Cloud Billing API to see what account the warehouse is being billed to.

Question 3

You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

Options:

A.

Load the data every 30 minutes into a new partitioned table in BigQuery.

B.

Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery

C.

Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore

D.

Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.