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Answer: Export your bill to a BigQuery dataset, and then write time window-based SQL queries for analysis.
The correct answer is D. Exporting your bill to a BigQuery dataset allows you to use standard SQL queries to analyze the data efficiently. BigQuery is well-suited for handling large volumes of structured data and performing complex queries quickly. It supports time-based SQL queries, enabling you to create service cost estimates by service type, both daily and monthly, for the next six months. Other options like Cloud Bigtable and Google Sheets don't adequately meet the requirements for structured data analysis using SQL.
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You are tasked with optimizing the analysis of costs for Google Cloud Platform (GCP) services across three distinct projects. The goal is to leverage this cost information to generate service-specific cost estimates on a daily and monthly basis for the upcoming six months. Utilizing standard query syntax, how should you proceed?
A
Export your bill to a Cloud Storage bucket, and then import into Cloud Bigtable for analysis.
B
Export your bill to a Cloud Storage bucket, and then import into Google Sheets for analysis.
C
Export your transactions to a local file, and perform analysis with a desktop tool.
D
Export your bill to a BigQuery dataset, and then write time window-based SQL queries for analysis.
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