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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:
Nov 28, 2025
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

Your company uses a proprietary system to send inventory data every 6 hours to a data ingestion service in the cloud. Transmitted data includes a payload of several fields and the timestamp of the transmission. If there are any concerns about a transmission, the system re-transmits the data. How should you deduplicate the data most efficiency?

Options:

A.

Assign global unique identifiers (GUID) to each data entry.

B.

Compute the hash value of each data entry, and compare it with all historical data.

C.

Store each data entry as the primary key in a separate database and apply an index.

D.

Maintain a database table to store the hash value and other metadata for each data entry.

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Question 2

After migrating ETL jobs to run on BigQuery, you need to verify that the output of the migrated jobs is the same as the output of the original. You’ve loaded a table containing the output of the original job and want to compare the contents with output from the migrated job to show that they are identical. The tables do not contain a primary key column that would enable you to join them together for comparison.

What should you do?

Options:

A.

Select random samples from the tables using the RAND() function and compare the samples.

B.

Select random samples from the tables using the HASH() function and compare the samples.

C.

Use a Dataproc cluster and the BigQuery Hadoop connector to read the data from each table and calculate a hash from non-timestamp columns of the table after sorting. Compare the hashes of each table.

D.

Create stratified random samples using the OVER() function and compare equivalent samples from each table.

Question 3

Your weather app queries a database every 15 minutes to get the current temperature. The frontend is powered by Google App Engine and server millions of users. How should you design the frontend to respond to a database failure?

Options:

A.

Issue a command to restart the database servers.

B.

Retry the query with exponential backoff, up to a cap of 15 minutes.

C.

Retry the query every second until it comes back online to minimize staleness of data.

D.

Reduce the query frequency to once every hour until the database comes back online.

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