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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:
Dec 6, 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

You are using Cloud Bigtable to persist and serve stock market data for each of the major indices. To serve the trading application, you need to access only the most recent stock prices that are streaming in How should you design your row key and tables to ensure that you can access the data with the most simple query?

Options:

A.

Create one unique table for all of the indices, and then use the index and timestamp as the row key design

B.

Create one unique table for all of the indices, and then use a reverse timestamp as the row key design.

C.

For each index, have a separate table and use a timestamp as the row key design

D.

For each index, have a separate table and use a reverse timestamp as the row key design

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Question 2

You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You’ve collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?

Options:

A.

Use Cloud Vision AutoML with the existing dataset.

B.

Use Cloud Vision AutoML, but reduce your dataset twice.

C.

Use Cloud Vision API by providing custom labels as recognition hints.

D.

Train your own image recognition model leveraging transfer learning techniques.

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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