Google Cloud Professional Data Engineer — Question 282

Your company is implementing a data warehouse using BigQuery, and you have been tasked with designing the data model. You move your on-premises sales data warehouse with a star data schema to BigQuery but notice performance issues when querying the data of the past 30 days. Based on Google's recommended practices, what should you do to speed up the query without increasing storage costs?

Answer options

• A. Denormalize the data.
• B. Shard the data by customer ID.
• C. Materialize the dimensional data in views.
• D. Partition the data by transaction date.

Correct answer: D

Explanation

Partitioning the data by transaction date (option D) allows BigQuery to only scan the relevant partitions for the last 30 days, significantly improving query performance. Denormalizing the data (option A) can lead to redundancy and may not resolve the performance issue effectively. Sharding by customer ID (option B) does not address the specific querying of recent transaction data. Materializing the dimensional data in views (option C) can improve access but does not optimize performance for specific date queries.