For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
To reduce unplanned vehicle downtime in GCP, using BigQuery as the data warehouse is appropriate since it can handle large volumes of data efficiently. Connecting all vehicles to the network and streaming data into BigQuery using Cloud Pub/Sub and Cloud Dataflow allows for real-time data ingestion and processing. Using Google Data Studio for analysis and reporting provides a powerful and flexible tool for generating insights. This combination ensures timely data analysis and response to issues, which is crucial for minimizing unplanned vehicle downtime.
Definitely A
Once all the vehicle are connected to network, there is no need to use FTP; data can be ingested directly to BQ using Pub/Sub and DataFlow.
A is good...simple streaming of data with managed services approach
Answer is A
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.
A is correct, using dataflow to clean and/or convert the data for analysis makes more sense. B does not show any sign of how data will be loaded to bigquery (as gzip) or after conversion, it seems broken process to me.
Technical requirement : Create a backup strategy Is bigquery a suitable system for data backup . Wouldn't a better system for backup be cloud storage. Only B has that option
A is ok
answer is A
vote A
A should be better. https://cloud.google.com/architecture/designing-connected-vehicle-platform#data_ingestion
Definitely A
A is right, all other options doesn't make sense.
Ans is A.
A is good
A is ok
A looks like the correct one
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. This approach leverages the real-time data streaming capabilities of Cloud Pub/Sub and Cloud Dataflow, the scalability and efficiency of BigQuery for data analysis, and the powerful visualization and reporting features of Google Data Studio. This combination ensures timely insights and quick response to issues, thereby reducing unplanned vehicle downtime.