Google Sample Question 24 of 27

You are administering a BigQuery on-demand environment. Your business intelligence tool is submitting hundreds of queries each day that aggregate a large (50 TB) sales history fact table at the day and month levels. These queries have a slow response time and are exceeding cost expectations. You need to decrease response time, lower query costs, and minimize maintenance. What should you do?

Source: Google Cloud OFFICIAL

Official sample question published by Google Cloud. WiseOwlLearns is not affiliated with Google LLC.

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A Build materialized views on top of the sales table to aggregate data at the day and month level. ✓ Correct
B Build authorized views on top of the sales table to aggregate data at the day and month level.
C Enable BI Engine and add your sales table as a preferred table.
D Create a scheduled query to build sales day and sales month aggregate tables on an hourly basis.
🦉 Explanation by WiseOwl Tutor™ — not endorsed by Google

A Is correct as materialized views pre-aggregate data so queries do not scan as much data and run faster B Is not correct as authorized views are not a performance improvement C is not correct as BI Engine caches frequently accessed dimension tables and won’t hold a 50 TB table in memory. D Is not correct because you have to maintain the scheduled queries

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