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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:
Apr 18, 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

Your company handles data processing for a number of different clients. Each client prefers to use their own suite of analytics tools, with some allowing direct query access via Google BigQuery. You need to secure the data so that clients cannot see each other’s data. You want to ensure appropriate access to the data. Which three steps should you take? (Choose three.)

Options:

A.

Load data into different partitions.

B.

Load data into a different dataset for each client.

C.

Put each client’s BigQuery dataset into a different table.

D.

Restrict a client’s dataset to approved users.

E.

Only allow a service account to access the datasets.

F.

Use the appropriate identity and access management (IAM) roles for each client’s users.

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Question 2

Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.

SELECT person FROM `project1.example.table1` WHERE city = "London"

How would you correct the error?

Options:

A.

Add ", UNNEST(person)" before the WHERE clause.

B.

Change "person" to "person.city".

C.

Change "person" to "city.person".

D.

Add ", UNNEST(city)" before the WHERE clause.

Question 3

You work for a shipping company that has distribution centers where packages move on delivery lines to route them properly. The company wants to add cameras to the delivery lines to detect and track any visual damage to the packages in transit. You need to create a way to automate the detection of damaged packages and flag them for human review in real time while the packages are in transit. Which solution should you choose?

Options:

A.

Use BigQuery machine learning to be able to train the model at scale, so you can analyze the packages in batches.

B.

Train an AutoML model on your corpus of images, and build an API around that model to integrate with the package tracking applications.

C.

Use the Cloud Vision API to detect for damage, and raise an alert through Cloud Functions. Integrate the package tracking applications with this function.

D.

Use TensorFlow to create a model that is trained on your corpus of images. Create a Python notebook in Cloud Datalab that uses this model so you can analyze for damaged packages.

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