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Google Professional Data Engineer

Google Professional Data Engineer

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You are managing two BigQuery projects with distinct requirements: one for production jobs with strict SLAs needing high priority and consistent access to 300 slots (spiking to 800), and another for ad-hoc analytical queries preferring billing based on data scanned, typically using up to 200 slots. How should you allocate compute resources to meet both projects' needs?

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