Your company implemented BigQuery as an enterprise data warehouse.
Users from multiple business units run queries on this data warehouse.
However, you notice that query costs for BigQuery are very high, and you need to control costs.
Which two methods should you use? (Choose two.)
Click on the arrows to vote for the correct answer
A. B. C. D. E.BE.
BigQuery is a fully-managed, cloud-native data warehouse that provides an efficient and cost-effective way to store and analyze large datasets. However, as data volumes grow and multiple users query the data warehouse, query costs can quickly become a significant expense. To control costs, there are several methods you can use.
A. Split the users from business units to multiple projects:
This method involves creating multiple BigQuery projects and assigning each project to a different business unit. By doing so, each business unit has its own dedicated resources, and the costs can be better controlled.
B. Apply a user- or project-level custom query quota for BigQuery data warehouse:
This method involves setting quotas at the user or project level for the number of queries that can be run against the data warehouse. This can help limit costs by preventing excessive usage, and also provides a way to track and manage usage across different users and projects.
C. Create separate copies of your BigQuery data warehouse for each business unit:
This method involves creating separate instances of the BigQuery data warehouse for each business unit. While this approach ensures complete isolation of resources, it also increases management complexity and can be more expensive to maintain.
D. Split your BigQuery data warehouse into multiple data warehouses for each business unit:
This method involves creating multiple data warehouses, each dedicated to a specific business unit. While this approach provides better resource isolation, it can also lead to increased management complexity and higher maintenance costs.
E. Change your BigQuery query model from on-demand to flat rate. Apply the appropriate number of slots to each Project:
This method involves changing the BigQuery pricing model from on-demand to flat rate, which offers more predictable costs for heavy users. Flat-rate pricing is based on the number of slots purchased, which are resources used to execute queries. By assigning the appropriate number of slots to each project, costs can be better controlled and allocated.
In summary, the two methods that should be used to control BigQuery costs are splitting users from business units to multiple projects and applying user- or project-level custom query quotas. However, the choice of method will depend on factors such as data volumes, usage patterns, and available resources.