PCDOE Optimizing performance and cost Practice Question
A company uses BigQuery for analytics with many queries scanning terabytes daily. They need to reduce query costs without reducing usage. What is the most effective strategy?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Partition and cluster tables.
Partitioning and clustering tables reduce the amount of data scanned per query, directly lowering costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reserve capacity in specific regions.
Why it's wrong here
Reserving capacity changes pricing model but does not reduce data scanned.
- ✗
Use flat-rate pricing with slots.
Why it's wrong here
Flat-rate pricing provides predictable costs but does not reduce actual query data processing.
- ✓
Partition and cluster tables.
Why this is correct
Partitioning and clustering limit the data scanned per query, reducing cost.
- ✗
Use standard SQL instead of legacy SQL.
Why it's wrong here
Query cost is based on data scanned, not SQL dialect.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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