You are using BigQuery with a multi-region dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of…

Question

Options

• ASchedule a daily export of the table to a Cloud Storage dual or multi-region bucket.
• BSchedule a daily copy of the dataset to a backup region.
• CSchedule a daily BigQuery snapshot of the table.
• DModify ETL job to load the data into both the current and another backup region.

• A
  77% (30)
• B
  8% (3)
• C
  13% (5)
• D
  3% (1)

Explanation

Exporting daily to a dual or multi-region Cloud Storage bucket satisfies all three constraints: the daily cadence meets the RPO < 24 hours requirement, the dual/multi-region bucket survives a regional outage, and Cloud Storage costs significantly less than keeping a live BigQuery dataset in multiple regions.

Why the distractors fail:

• B is wrong because copying the full dataset to a second BigQuery region every day is functionally similar to A but far more expensive - you pay for active BigQuery storage in both regions.
• C is wrong because BigQuery table snapshots reside in the same region as the source table; a regional failure would destroy both the table and its snapshots.
• D is wrong because dual-loading via ETL into two separate regions requires maintaining two live datasets, increasing both cost and operational complexity well beyond what the RPO demands.

Memory tip: Map the three constraints to the answer - RPO < 24h → daily schedule, regional failure → dual/multi-region destination, minimize cost → Cloud Storage (not BigQuery). Whenever you see those three together on an exam, "daily export to multi-region GCS" is the pattern to reach for.

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