GCP Professional Data Engineer Practice Question

Your analytics platform runs a fixed set of transformation queries every night at 03:00 UTC. The job scans roughly 5 TB of data and completes in about 25 minutes. During business hours, data scientists submit unpredictable, small interactive queries and expect low-latency responses. Management asks you to reduce monthly query spending but keep the daytime user experience unchanged. Which BigQuery pricing strategy best meets these requirements?

  • Buy a 12-month commitment for 500 dedicated slots and assign all projects to the reservation, covering both nightly and daytime queries.

  • Move the source tables to an archive storage class and keep all queries on on-demand pricing to lower overall costs.

  • Run the nightly transformations as batch-priority queries under on-demand pricing to avoid concurrency limits during the day.

  • Purchase a flex slot reservation that activates only during the nightly window, assign it to the transformation workload, and leave daytime queries on on-demand pricing.

GCP Professional Data Engineer
Maintaining and automating data workloads
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