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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:
387
Last Updated:
Jan 10, 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 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?

Options:

A.

Linear regression

B.

Logistic classification

C.

Recurrent neural network

D.

Feedforward neural network

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Question 2

You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are:

Decoupling producer from consumer

Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely

Near real-time SQL query

Maintain at least 2 years of historical data, which will be queried with SQ

Which pipeline should you use to meet these requirements?

Options:

A.

Create an application that provides an API. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.

B.

Create an application that writes to a Cloud SQL database to store the data. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.

C.

Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.

D.

Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.

Question 3

MJTelco is building a custom interface to share data. They have these requirements:

They need to do aggregations over their petabyte-scale datasets.

They need to scan specific time range rows with a very fast response time (milliseconds).

Which combination of Google Cloud Platform products should you recommend?

Options:

A.

Cloud Datastore and Cloud Bigtable

B.

Cloud Bigtable and Cloud SQL

C.

BigQuery and Cloud Bigtable

D.

BigQuery and Cloud Storage

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