Free Google Professional-Data-Engineer Exam Questions

Become Google Certified with updated Professional-Data-Engineer exam questions and correct answers

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Total 472 Questions | Updated On: Aug 20, 2026

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Question 1

Why do you need to split a machine learning dataset into training data and test data?

A : you can try two different sets of features

B : make sure your model is generalized for more than just the training data

C : allow you to create unit tests in your code

D : you can use one dataset for a wide model and one for a deep model

Answer: B

Question 2

Which of these statements about exporting data from BigQuery is false?

A : export more than 1 GB of data, you need to put a wildcard in the destination filename.

B : only supported export destination is Google Cloud Storage.

C : ta can only be exported in JSON or Avro format.

D : only compression option available is GZIP.

Answer: C

Question 3

You are designing a basket abandonment system for an ecommerce company. The system will send a message

to a user based on these rules:

No interaction by the user on the site for 1 hour

Has added more than $30 worth of products to the basket

Has not completed a transaction

You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you

design the pipeline?

A : a fixed-time window with a duration of 60 minutes.

B : a sliding time window with a duration of 60 minutes.

C : a session window with a gap time duration of 60 minutes.

D : a global window with a time based trigger with a delay of 60 minutes.

Answer: C

Question 4

You use a dataset in BigQuery for analysis. You want to provide third-party companies with access to the same dataset. You need to keep the costs of data sharing low and ensure that the data is current. Which solution should you choose?

A : eate an authorized view on the BigQuery table to control data access, and provide third-party companies with access to that view.

B : Cloud Scheduler to export the data on a regular basis to Cloud Storage, and provide third-party companies with access to the bucket.

C : eate a separate dataset in BigQuery that contains the relevant data to share, and provide third-party companies with access to the new dataset.

D : eate a Cloud Dataflow job that reads the data in frequent time intervals, and writes it to the relevant BigQuery dataset or Cloud Storage bucket for third-party companies to use.

Answer: B

Question 5

Which of these are examples of a value in a sparse vector? (Select 2 answers.)

A : [0, 5, 0, 0, 0, 0]

B : [0, 0, 0, 1, 0, 0, 1]

C : [0, 1]

D : [1, 0, 0, 0, 0, 0, 0]

Answer: C,D

Page: 1 / 95

Total 472 Questions | Updated On: Aug 20, 2026

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