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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:
Google Cloud Certified
Vendor:
Google
Questions:
400
Last Updated:
Feb 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

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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Your custom endpoint has an out-of-date SSL certificate.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 migrated a data backend for an application that serves 10 PB of historical product data for analytics. Only the last known state for a product, which is about 10 GB of data, needs to be served through an API to the other applications. You need to choose a cost-effective persistent storage solution that can accommodate the analytics requirements and the API performance of up to 1000 queries per second (QPS) with less than 1 second latency. What should you do?

Options:

A.

1. Store the historical data in BigQuery for analytics.2. In a Cloud SQL table, store the last state of the product after every product change.3. Serve the last state data directly from Cloud SQL to the API.

B.

1. Store the historical data in Cloud SQL for analytics.2. In a separate table, store the last state of the product after every product change.3. Serve the last state data directly from Cloud SQL to the API.

C.

1. Store the products as a collection in Firestore with each product having a set of historical changes.2. Use simple and compound queries for analytics.3. Serve the last state data directly from Firestore to the API.

D.

1. Store the historical data in BigQuery for analytics.2. Use a materialized view to precompute the last state of a product.3. Serve the last state data directly from BigQuery to the API.

Question 3

You are developing an application on Google Cloud that will automatically generate subject labels for users’ blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

Options:

A.

Call the Cloud Natural Language API from your application. Process the generated Entity Analysis aslabels.

B.

Call the Cloud Natural Language API from your application. Process the generated Sentiment Analysis as labels.

C.

Build and train a text classification model using TensorFlow. Deploy the model using Cloud MachineLearning Engine. Call the model from your application and process the results as labels.

D.

Build and train a text classification model using TensorFlow. Deploy the model using a Kubernetes Engine cluster. Call the model from your application and process the results as labels.

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