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

What are two of the benefits of using denormalized data structures in BigQuery?
A . Reduces the amount of data processed, reduces the amount of storage required
B . Increases query speed, makes queries simpler
C . Reduces the amount of storage required, increases query speed
D . Reduces the amount of data processed, increases query speed

Answer: B

Explanation:

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 redundant data.

Reference:

https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data