Explanation:
Option D is correct because configuring Cloud Billing data export to BigQuery allows for detailed billing data to be exported to a BigQuery dataset. This provides granular access to cost and usage data, enabling dynamic calculations based on company-specific criteria. Looker Studio can then be used to create a dashboard that connects to the BigQuery dataset, offering automated and customizable cost visualizations. Options A and B are incorrect as they offer less flexibility and customization. Option C is incorrect because it lacks the automation and real-time data integration provided by BigQuery. Learn more about exporting data to BigQuery and Looker Studio.
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At a large enterprise with multiple projects on Google Cloud, all linked to the same billing account, the finance team requests a dynamic visualization of costs to calculate specific metrics based on company-specific data. How can you automate the creation of such visualizations?
A
Use the Reports section in the Google Cloud console to visualize project costs.
B
Utilize the Cost breakdown section in the Google Cloud console for project cost visualizations.
C
Export the Cost table from the Google Cloud console as a CSV and create a Looker Studio dashboard from the export.
D
Set up Cloud Billing data export to BigQuery for the billing account and create a Looker Studio dashboard based on the BigQuery export.