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Answer: Create a BigQuery reservation with a baseline of 500 slots with no autoscaling for the marketing team, and bill them back accordingly.
The correct answer is **C**. By setting up a BigQuery reservation with a baseline of 500 slots for the marketing team, you ensure they have dedicated capacity at all times, leading to a consistent monthly spend. Disabling autoscaling prevents unexpected cost spikes. Billing them based on reserved capacity ensures predictable charges. - **Option A** is incorrect because setting a daily byte scan limit doesn't guarantee dedicated capacity, leading to potential cost variability. - **Option B** is not ideal as a pay-as-you-go reservation with no baseline slots offers no guaranteed capacity, resulting in fluctuating costs. - **Option D** is less optimal because a baseline of 250 slots might not meet the team's needs, and autoscaling could introduce billing unpredictability.
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As the administrator of shared BigQuery datasets that include views used by various teams in your organization, the marketing team has raised concerns about unpredictable monthly BigQuery analytics costs under the on-demand billing model. What strategy can you implement to help the marketing team achieve a consistent monthly BigQuery analytics expenditure?
A
Establish a BigQuery quota for the marketing team, limiting the maximum number of bytes scanned each day.
B
Create a BigQuery Standard pay-as-you-go reservation with a baseline of 0 slots and autoscaling set to 500 for the marketing team, and bill them back accordingly.
C
Create a BigQuery reservation with a baseline of 500 slots with no autoscaling for the marketing team, and bill them back accordingly.
D
Create a BigQuery Enterprise reservation with a baseline of 250 slots and autoscaling set to 500 for the marketing team, and bill them back accordingly.
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