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Google Professional-Data-Engineer Exam With Confidence Using Practice Dumps

Exam Code:
Professional-Data-Engineer
Exam Name:
Google Professional Data Engineer Exam
Certification:
Vendor:
Questions:
387
Last Updated:
Jan 9, 2026
Exam Status:
Stable
Google Professional-Data-Engineer

Professional-Data-Engineer: Google Cloud Certified Exam 2025 Study Guide Pdf and Test Engine

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Google Professional Data Engineer Exam Questions and Answers

Question 1

You work for a car manufacturer and have set up a data pipeline using Google Cloud Pub/Sub to capture anomalous sensor events. You are using a push subscription in Cloud Pub/Sub that calls a custom HTTPS endpoint that you have created to take action of these anomalous events as they occur. Your custom HTTPS endpoint keeps getting an inordinate amount of duplicate messages. What is the most likely cause of these duplicate messages?

Options:

A.

The message body for the sensor event is too large.

B.

Your custom endpoint has an out-of-date SSL certificate.

C.

The Cloud Pub/Sub topic has too many messages published to it.

D.

Your custom endpoint is not acknowledging messages within the acknowledgement deadline.

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Question 2

You are deploying a new storage system for your mobile application, which is a media streaming service. You decide the best fit is Google Cloud Datastore. You have entities with multiple properties, some of which can take on multiple values. For example, in the entity ‘Movie’ the property ‘actors’ and the property ‘tags’ have multiple values but the property ‘date released’ does not. A typical query would ask for all movies with actor= ordered by date_released or all movies with tag=Comedy ordered by date_released. How should you avoid a combinatorial explosion in the number of indexes?

Options:

A.

Option A

B.

Option B.

C.

Option C

D.

Option D

Question 3

Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

Options:

A.

Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

B.

Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project

C.

Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

D.

Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric