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: Jun 17, 2026

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Question 1

How would you query specific partitions in a BigQuery table?

A : the DAY column in the WHERE clause

B : the EXTRACT(DAY) clause

C : the __PARTITIONTIME pseudo-column in the WHERE clause

D : DATE BETWEEN in the WHERE clause

Answer: C

Question 2

Which of the following is NOT a valid use case to select HDD (hard disk drives) as the storage for Google Cloud Bigtable?

A : u expect to store at least 10 TB of data.

B : u will mostly run batch workloads with scans and writes, rather than frequently executing random reads of a small number of rows.

C : u need to integrate with Google BigQuery.

D : u will not use the data to back a user-facing or latency-sensitive application.

Answer: C

Question 3

Your company is currently setting up data pipelines for their campaign. For all the Google Cloud Pub/Sub streaming data, one of the important business requirements is to be able to periodically identify the inputs and their timings during their campaign. Engineers have decided to use windowing and transformation in Google Cloud Dataflow for this purpose. However, when testing this feature, they find that the Cloud Dataflow job fails for the all streaming insert. What is the most likely cause of this problem?

A : ey have not assigned the timestamp, which causes the job to fail

B : ey have not set the triggers to accommodate the data coming in late, which causes the job to fail

C : ey have not applied a global windowing function, which causes the job to fail when the pipeline is created

D : ey have not applied a non-global windowing function, which causes the job to fail when the pipeline is created

Answer: C

Question 4

By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

A : ndows at every 100 MB of data

B : ngle, Global Window

C : ndows at every 1 minute

D : ndows at every 10 minutes

Answer: B

Question 5

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

Page: 1 / 95

Total 472 Questions | Updated On: Jun 17, 2026

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