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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:
May 17, 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

Which of these is not a supported method of putting data into a partitioned table?

Options:

A.

If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.

B.

Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".

C.

Create a partitioned table and stream new records to it every day.

D.

Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".

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Question 2

Flowlogistic’s management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?

Options:

A.

Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage

B.

Cloud Pub/Sub, Cloud Dataflow, and Local SSD

C.

Cloud Pub/Sub, Cloud SQL, and Cloud Storage

D.

Cloud Load Balancing, Cloud Dataflow, and Cloud Storage

Question 3

Your company’s customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations. What should you do?

Options:

A.

Add a node to the MySQL cluster and build an OLAP cube there.

B.

Use an ETL tool to load the data from MySQL into Google BigQuery.

C.

Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.

D.

Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.

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