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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:
Mar 25, 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

What are all of the BigQuery operations that Google charges for?

Options:

A.

Storage, queries, and streaming inserts

B.

Storage, queries, and loading data from a file

C.

Storage, queries, and exporting data

D.

Queries and streaming inserts

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Question 2

You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.

You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)

Options:

A.

Redis

B.

HBase

C.

MySQL

D.

MongoDB

E.

Cassandra

F.

HDFS with Hive

Question 3

You use a dataset in BigQuery for analysis. You want to provide third-party companies with access to the same dataset. You need to keep the costs of data sharing low and ensure that the data is current. Which solution should you choose?

Options:

A.

Create an authorized view on the BigQuery table to control data access, and provide third-party companies with access to that view.

B.

Use Cloud Scheduler to export the data on a regular basis to Cloud Storage, and provide third-party companies with access to the bucket.

C.

Create a separate dataset in BigQuery that contains the relevant data to share, and provide third-party companies with access to the new dataset.

D.

Create a Cloud Dataflow job that reads the data in frequent time intervals, and writes it to the relevant BigQuery dataset or Cloud Storage bucket for third-party companies to use.

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