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PROFESSIONAL-DATA-ENGINEER · Question #396
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…
The correct answer is A. Build materialized views on top of the sales table to aggregate data at the day and month level. Explanation/Reference: To improve response times and reduce costs for frequent queries aggregating a large sales history fact table, materialized views are a highly effective solution. Here's why option A is the best choice:
Submitted by satoshi_tk· Mar 30, 2026Designing data processing systems
Question
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?
Options
- ABuild materialized views on top of the sales table to aggregate data at the day and month level.
- BBuild authorized views on top of the sales table to aggregate data at the day and month level.
- CEnable Bl Engine and add your sales table as a preferred table.
- DCreate a scheduled query to build sales day and sales month aggregate tables on an hourly basis.
How the community answered
(42 responses)- A81% (34)
- B2% (1)
- C12% (5)
- D5% (2)
Explanation
Explanation/Reference: To improve response times and reduce costs for frequent queries aggregating a large sales history fact table, materialized views are a highly effective solution. Here's why option A is the best choice:
Topics
#materialized views#BigQuery optimization#BI performance#cost reduction
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