Free PDF Quiz Google - The Best Exam Professional-Data-Engineer Simulations

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The Google Professional-Data-Engineer Exam is designed for data engineers, data analysts, and data scientists who work with data processing systems and data analytics solutions on the Google Cloud Platform. Google Certified Professional Data Engineer Exam certification demonstrates their ability to design, build, and manage scalable, reliable, and cost-effective data solutions on Google Cloud.

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Free PDF Professional-Data-Engineer - Reliable Exam Google Certified Professional Data Engineer Exam Simulations

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Google Professional-Data-Engineer certification exam is a rigorous and comprehensive exam that requires individuals to have a deep understanding of data engineering technologies and concepts. Professional-Data-Engineer exam consists of multiple choice and scenario-based questions that assess an individual's ability to design, build, and maintain data processing systems on Google Cloud Platform. Professional-Data-Engineer Exam is timed and individuals have a limited amount of time to complete the exam. To pass the exam, individuals must score 70% or higher.

Google Certified Professional Data Engineer Exam Sample Questions (Q183-Q188):

NEW QUESTION # 183
Cloud Dataproc charges you only for what you really use with _____ billing.

A. hour-by-hour
B. week-by-week
C. month-by-month
D. minute-by-minute

Answer: D

Explanation:
One of the advantages of Cloud Dataproc is its low cost. Dataproc charges for what you really use with minute-by-minute billing and a low, ten-minute-minimum billing period.

NEW QUESTION # 184
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a ____ proxy.

A. VPN
B. HTTPS
C. HTTP
D. SOCKS

Answer: D

Explanation:
When using Cloud Dataproc clusters, configure your browser to use the SOCKS proxy. The SOCKS proxy routes data intended for the Cloud Dataproc cluster through an SSH tunnel.

NEW QUESTION # 185
You want to archive data in Cloud Storage. Because some data is very sensitive, you want to use the "Trust No One" (TNO) approach to encrypt your data to prevent the cloud provider staff from decrypting your data. What should you do?

A. Specify customer-supplied encryption key (CSEK) in the .botoconfiguration file. Use gsutil cpto upload each archival file to the Cloud Storage bucket. Save the CSEK in a different project that only the security team can access.
B. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encryptto encrypt each archival file with the key. Use gsutil cpto upload each encrypted file to the Cloud Storage bucket.
Manually destroy the key previously used for encryption, and rotate the key once.
C. Specify customer-supplied encryption key (CSEK) in the .botoconfiguration file. Use gsutil cpto upload each archival file to the Cloud Storage bucket. Save the CSEK in Cloud Memorystore as permanent storage of the secret.
D. Use gcloud kms keys createto create a symmetric key. Then use gcloud kms encryptto encrypt each archival file with the key and unique additional authenticated data (AAD). Use gsutil cp to upload each encrypted file to the Cloud Storage bucket, and keep the AAD outside of Google Cloud.

Answer: B

Explanation:
Explanation/Reference:

NEW QUESTION # 186
You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

A. Change the data pipeline to use BigQuery for storing stock trades, and update your application.
B. Change the row key syntax in your Cloud Bigtable table to begin with the stock symbol.
C. Change the row key syntax in your Cloud Bigtable table to begin with a random number per second.
D. Use Cloud Dataflow to write summary of each day's stock trades to an Avro file on Cloud Storage.
Update your application to read from Cloud Storage and Cloud Bigtable to compute the responses.

Answer: B

NEW QUESTION # 187
Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow.
Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour.
The data scientists have written the following code to read the data for a new key features in the logs.
BigQueryIO.Read
.named("ReadLogData")
.from("clouddataflow-readonly:samples.log_data")
You want to improve the performance of this data read. What should you do?

A. Call a transform that returns TableRow objects, where each element in the PCollection represents a single row in the table.
B. Specify the TableReference object in the code.
C. Use of both the Google BigQuery TableSchema and TableFieldSchema classes.
D. Use .fromQuery operation to read specific fields from the table.

Answer: A

NEW QUESTION # 188
......

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