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Answer: Access historical data by using time travel in BigQuery.
The correct answer is A: Access historical data by using time travel in BigQuery. The time travel feature in BigQuery allows accessing historical data for up to seven days, making it possible to recover from data corruption within this period. This feature incurs no additional costs as it is built into BigQuery, and it eliminates the need for manual backup and restore processes, making it the most cost-effective and managed solution with the lowest RPO.
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You are tasked with designing a fault-tolerant architecture for storing data in a regional BigQuery dataset in Google Cloud. The goal is to ensure that your application can recover from any data corruption events that occur within a seven-day window. Your priority is to use managed services that offer the lowest Recovery Point Objective (RPO) while also being cost-effective. What steps should you take to achieve this?
A
Access historical data by using time travel in BigQuery.
B
Export the data from BigQuery into a new table that excludes the corrupted data.
C
Create a BigQuery table snapshot on a daily basis.
D
Migrate your data to multi-region BigQuery buckets.