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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 26, 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 work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

Options:

A.

Load the data every 30 minutes into a new partitioned table in BigQuery.

B.

Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery

C.

Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore

D.

Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.

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Question 2

How can you get a neural network to learn about relationships between categories in a categorical feature?

Options:

A.

Create a multi-hot column

B.

Create a one-hot column

C.

Create a hash bucket

D.

Create an embedding column

Question 3

You store historic data in Cloud Storage. You need to perform analytics on the historic data. You want to use a solution to detect invalid data entries and perform data transformations that will not require programming or knowledge of SQL.

What should you do?

Options:

A.

Use Cloud Dataflow with Beam to detect errors and perform transformations.

B.

Use Cloud Dataprep with recipes to detect errors and perform transformations.

C.

Use Cloud Dataproc with a Hadoop job to detect errors and perform transformations.

D.

Use federated tables in BigQuery with queries to detect errors and perform transformations.

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