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Google Updated Professional-Cloud-Architect Exam Questions and Answers by jakob

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Google Professional-Cloud-Architect Exam Overview :

Exam Name: Google Certified Professional - Cloud Architect (GCP)
Exam Code: Professional-Cloud-Architect Dumps
Vendor: Google Certification: Google Cloud Certified
Questions: 275 Q&A's Shared By: jakob
Question 32

TerramEarth has about 1 petabyte (PB) of vehicle testing data in a private data center. You want to move the data to Cloud Storage for your machine learning team. Currently, a 1-Gbps interconnect link is available for you. The machine learning team wants to start using the data in a month. What should you do?

Options:

A.

Request Transfer Appliances from Google Cloud, export the data to appliances, and return the appliances to Google Cloud.

B.

Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage

C.

Make sure there are no other users consuming the 1 Gbps link, and use multi-thread transfer to upload the data to Cloud Storage.

D.

Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data to Cloud Storage

Discussion
Question 33

For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

Options:

A.

Replace the existing data warehouse with BigQuery. Use table partitioning.

B.

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.

C.

Replace the existing data warehouse with BigQuery. Use federated data sources.

D.

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.

Discussion
Question 34

For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to

BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an

automated daily basis while managing cost.

What should you do?

Options:

A.

Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a Cloud Dataflow pipeline.

B.

Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud Function from a Compute Engine instance.

C.

Create a SQL statement on the data in BigQuery, and save it as a view. Run the view daily, and save the result to a new table.

D.

Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the data.

Discussion
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Question 35

For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?

Options:

A.

Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.

B.

Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.

C.

Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage

bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.

D.

Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables. Use Pig scripts to analyze data.

Discussion
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