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Prepare and test your skills
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Your organization runs three distinct BigQuery workloads: Data Science, ELT, and Business Intelligence (BI). Currently, all queries use the default on-demand pricing model, resulting in highly variable and unpredictable monthly costs. You need to implement a cost-optimized processing architecture that provides predictable pricing while guaranteeing dedicated compute capacity for each workload. Additionally, to maximize resource utilization, any idle compute capacity from one workload must be automatically available to the others.
What should you do?
BigQuery slot commitments allow organizations to transition from on-demand pricing to capacity-based pricing by purchasing dedicated compute resources (slots). Reservations are allocations of these purchased slots that can be assigned to specific projects, folders, or workloads.
This architecture perfectly balances performance and cost. It provides the financial predictability of flat-rate pricing while leveraging BigQuery's intelligent workload management to dynamically share idle resources, ensuring optimal performance for all three distinct workloads.
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