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Professional-Cloud-Architect Google Cloud Architect Professional

  • Google
  • 5 free sample questions

About this exam

Professional-Cloud-Architect is the Google exam Google Cloud Architect Professional. Paid practice material for this exam is not available yet, but you can try its free sample questions.

Exam code
Professional-Cloud-Architect
Vendor
Google
Practice questions
Not available yet
Free sample questions
5
Question bank last updated
Not available yet

Try 2 sample questions

Taken from the free sample set for Professional-Cloud-Architect.

Question 1

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?

  1. Option A:

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

  2. Option B:

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

  3. Option C:

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

  4. Option 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.

Show answer and explanation

Correct answer: C

https://cloud.google.com/solutions/bigquery-data-warehouse#external_sources

https://cloud .google.com/solutions/bigquery-data-warehouse

Question 2

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

  1. Option 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.

  2. Option 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.

  3. Option 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.

  4. Option D:

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

Show answer and explanation

Correct answer: A

See all 5 free sample questions