What are two of the benefits of using denormalized data structures in BigQuery?

The correct answer is B. Increases query speed, makes queries simpler. Explanation/Reference: Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data structure, you don't have to use JOINs, since all of the data has been combined int

Submitted by ricky.ec· Mar 30, 2026Designing data processing systems

Question

What are two of the benefits of using denormalized data structures in BigQuery?

Options

AReduces the amount of data processed, reduces the amount of storage required
BIncreases query speed, makes queries simpler
CReduces the amount of storage required, increases query speed
DReduces the amount of data processed, increases query speed

How the community answered

(59 responses)

A
3% (2)
B
86% (51)
C
8% (5)
D
2% (1)

Explanation

Explanation/Reference: Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data structure, you don't have to use JOINs, since all of the data has been combined into one table. Denormalization also makes queries simpler because you do not have to use JOIN clauses. Denormalization increases the amount of data processed and the amount of storage required because it creates https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data

Topics

#BigQuery denormalization#query performance#schema design#nested data

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