Exam Professional Cloud Architect topic 3 question 5 discussion

Answer is C

C. Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on season.

Vote for C

How can it be C because BigQuery only support timestamp based partitions?

C looks good. Remember Telemetry would be stored and used for predictions later A. would be good if it would be stored only, as documents. B. Spanner is over kill. It is too expensive and we have no need to serve this data outside D. Cloud SQL is too simple solution and use multiple db's is only complicating architecture.

C is the correct Answer, We can use BigQuery for making Predictions with live and trained data with Cloud ML Engine, and BigQuery can handle large amounts of data. Refer to the Link for more details on Game Predictions, https://cloud.google.com/blog/products/gcp/architecting-live-ncaa-predictions-from-archives-to-insights

For HRL's data storage needs, it is recommended to use BigQuery due to its scalability and ability to handle large amounts of data. By partitioning the race data based on season, HRL can easily access and query specific seasons' data while also taking into consideration future data growth. BigQuery also allows for the flexibility to add new columns to the schema as needed, making it easier to adapt to changes in the data being collected. Additionally, BigQuery's pay-per-use pricing model allows HRL to only pay for the data storage and querying they use, making it a cost-effective solution.

C is the correct answer

C is the correct answer

C is ok

C it is

c C C c

C most obvious when data is growing day by day.

Had this question on my exam.

Telemetry data in a relational table..what?? Why they gave firestore then

Got this question in my exam, answered C

to me it's C -> https://cloud.google.com/architecture/mobile-gaming-analysis-telemetry