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Question No. 1

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

A. Use BigQuery as the data warehouse. Connect all vehicles to the network and stream datainto BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysisand reporting.B. Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzipfiles to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio foranalysis and reporting.C. Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional CloudStorage bucket. Upload this data into BigQuery using gcloud. Use Google data Studio foranalysis and reporting.D. Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hivetables. Use Pig scripts to analyze data.

Answer: A

Question No. 2

For this question, refer to the TerramEarth case study. You are asked to design a new architecturefor the

ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want tofollow

Google-recommended practices.

Considering the technical requirements, which components should you use for the ingestion of thedata?

A. Google Kubernetes Engine with an SSL IngressB. Cloud IoT Core with public/private key pairsC. Compute Engine with project-wide SSH keysD. Compute Engine with specific SSH keys

Answer: A

Question No. 3

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

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

automated daily basis while managing cost.

What should you do?

A. Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean thedata 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 jobto clean the data.

Answer: A

Question No. 4

For this question, refer to the TerramEarth case study. TerramEarth has decided to store data filesin Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data andminimize file storage cost.

Which two actions should you take?

A. Create a Cloud Storage lifecycle rule with Age: ''30'', Storage Class: ''Standard'', andAction: ''Set to Coldline'', and create a second GCS life-cycle rule with Age: ''365'', StorageClass: ''Coldline'', and Action: ''Delete''.B. Create a Cloud Storage lifecycle rule with Age: ''30'', Storage Class: ''Coldline'', and Action:''Set to Nearline'', and create a second GCS life-cycle rule with Age: ''91'', Storage Class:''Coldline'', and Action: ''Set to Nearline''.C. Create a Cloud Storage lifecycle rule with Age: ''90'', Storage Class: ''Standard'', andAction: ''Set to Nearline'', and create a second GCS life-cycle rule with Age: ''91'', StorageClass: ''Nearline'', and Action: ''Set to Coldline''.D. Create a Cloud Storage lifecycle rule with Age: ''30'', Storage Class: ''Standard'', andAction: ''Set to Coldline'', and create a second GCS life-cycle rule with Age: ''365'', StorageClass: ''Nearline'', and Action: ''Delete''.

Answer: A

Question No. 5

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

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. Addan additional Compute Engine pre-emptible instance with 32 CPUs.

Answer: C

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