Free Google Professional-Data-Engineer Exam Questions

Become Google Certified with updated Professional-Data-Engineer exam questions and correct answers

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Total 472 Questions | Updated On: Jun 17, 2026

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Question 1

You are creating a model to predict housing prices. Due to budget constraints, you must run it on a single resource-constrained virtual machine. Which learning algorithm should you use?

A : near regression

B : gistic classification

C : current neural network

D : edforward neural network

Answer: A

Question 2

You want to use a BigQuery table as a data sink. In which writing mode(s) can you use BigQuery as a sink?

A : th batch and streaming

B : gQuery cannot be used as a sink

C : ly batch

D : ly streaming

Answer: A

Question 3

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

A : ecute to Google Cloud Storage; write to Google Cloud Logging

B : ite to Google Cloud Storage; read to Google Cloud Logging

C : ecute to Google Cloud Storage; execute to Google Cloud Logging

D : ad and write to Google Cloud Storage; write to Google Cloud Logging

Answer: D

Question 4

You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

A : ange the row key syntax in your Cloud Bigtable table to begin with the stock symbol.

B : ange the row key syntax in your Cloud Bigtable table to begin with a random number per second.

C : ange the data pipeline to use BigQuery for storing stock trades, and update your application.

D : Cloud Dataflow to write summary of each day’s stock trades to an Avro file on Cloud Storage. Update your application to read from Cloud Storage and Cloud Bigtable to compute the responses.

Answer: A

Question 5

You have a data processing application that runs on Google Kubernetes Engine (GKE). Containers need to be

launched with their latest available configurations from a container registry. Your GKE nodes need to have

GPUs. local SSDs, and 8 Gbps bandwidth. You want to efficiently provision the data processing infrastructure

and manage the deployment process. What should you do?

A : Use Compute Engi.no startup scriots to pull container Images, and use gloud commands to provision theinfrastructure.

B : Use GKE to autoscale containers, and use gloud commands to provision the infrastructure.

C : Use Cloud Build to schedule a job using Terraform build to provision the infrastructure and launch with the most current container images.

D : Use Dataflow to provision the data pipeline, and use Cloud Scheduler to run the job.

Answer: C

Page: 1 / 95

Total 472 Questions | Updated On: Jun 17, 2026

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