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Answer: Apply custom query quota for BigQuery data warehouse at the user level or project level., Change your BigQuery query model from on-demand to flat rate. Apply the appropriate number of slots to each Project.
Applying custom query quotas (Option A) helps limit costs by setting boundaries on query resources users or projects can consume. Switching to a flat rate pricing model (Option B) allows for predictable costs by allocating a fixed number of slots to each project, thus controlling concurrent queries. Creating multiple projects (Option C) or separate copies (Option D) of the data warehouse does not reduce costs and may increase them. Similarly, splitting the data warehouse (Option E) leads to higher expenses due to duplicated resources.
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As the head of a data warehouse in a global analytics firm, you're using BigQuery as the primary tool. With query costs exceeding the budget, which two strategies would best help control these costs? (Choose two)
A
Apply custom query quota for BigQuery data warehouse at the user level or project level.
B
Change your BigQuery query model from on-demand to flat rate. Apply the appropriate number of slots to each Project.
C
Create multiple projects based on users’ business units and split the users.
D
Create separate copies of your BigQuery data warehouse for each business unit.
E
Split your BigQuery data warehouse into multiple data warehouses based on the requirements of each business unit.
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