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Google Professional-Data-Engineer Dumps Questions Answers

Exam Code:
Professional-Data-Engineer
Last Update: Apr 25, 2024
330 Questions Answers with Explanation Detail
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Professional-Data-Engineer Q&A's Detail

Exam Code:
Professional-Data-Engineer
Total Questions:
330 Q&A's
Single Choice Questions:
300 Q&A's
Multiple Choice Questions:
30 Q&A's

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Google Professional Data Engineer Exam Questions and Answers

Questions 1

The marketing team at your organization provides regular updates of a segment of your customer dataset. The marketing team has given you a CSV with 1 million records that must be updated in BigQuery. When you use the UPDATE statement in BigQuery, you receive a quotaExceeded error. What should you do?

Options:

A.

Reduce the number of records updated each day to stay within the BigQuery UPDATE DML statement limit.

B.

Increase the BigQuery UPDATE DML statement limit in the Quota management section of the Google Cloud Platform Console.

C.

Split the source CSV file into smaller CSV files in Cloud Storage to reduce the number of BigQuery UPDATE DML statements per BigQuery job.

D.

Import the new records from the CSV file into a new BigQuery table. Create a BigQuery job that merges the new records with the existing records and writes the results to a new BigQuery table.

Questions 2

Your chemical company needs to manually check documentation for customer order. You use a pull subscription in Pub/Sub so that sales agents get details from the order. You must ensure that you do not process orders twice with different sales agents and that you do not add more complexity to this workflow. What should you do?

Options:

A.

Create a transactional database that monitors the pending messages.

B.

Create a new Pub/Sub push subscription to monitor the orders processed in the agent's system.

C.

Use Pub/Sub exactly-once delivery in your pull subscription.

D.

Use a Deduphcate PTransform in Dataflow before sending the messages to the sales agents.

Questions 3

You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

Options:

A.

Set the BigQuery dataset to be regional. In the event of an emergency, use a point-in-time snapshot to recover the data.

B.

Set the BigQuery dataset to be regional. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup. In the event of an emergency, use the backup copy of the table.

C.

Set the BigQuery dataset to be multi-regional. In the event of an emergency, use a point-in-time snapshot to recover the data.

D.

Set the BigQuery dataset to be multi-regional. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup. In the event of an emergency, use the backup copy of the table.

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