This is a dedicated watch page for a single video.
In managing BigQuery jobs across two distinct projects with diverse needs and priorities, a nuanced approach is necessary to ensure optimal resource allocation. The first project handles critical production jobs with strict completion time SLAs, necessitating consistent availability of compute resources, typically maintaining a baseline of 300 slots and occasionally spiking up to an additional 500 slots. Conversely, the second project caters to ad-hoc analytical queries from users, where resource usage seldom exceeds 200 slots, and billing preference leans towards data scanned rather than slot capacity. Given this scenario, how would you design a resource allocation strategy that effectively caters to the varying requirements of both projects, ensuring that compute resources are appropriately allocated while maintaining cost-efficiency and meeting performance targets?