hardMultiple ChoiceObjective-mapped
PCDE Practice Question: A retail company uses BigQuery to store sales data
A retail company uses BigQuery to store sales data. The 'sales' table has 10 billion rows and is partitioned by transaction_date (daily). The BI dashboard runs a query that aggregates sales by product_category for the last 30 days. The query is slow and expensive. Which improvement is most effective?
⚠ Common exam trap
Google Cloud often tests the distinction between partitioning (which limits data by time range) and clustering (which organizes data within partitions for column-based pruning), and candidates mistakenly choose partitioning changes or materialized views without understanding that clustering directly addresses the slow aggregation on a non-time column.
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
✓
Cluster the table on product_category
Clustering the table on product_category organizes the data within each daily partition by that column, allowing BigQuery to use block-level pruning to skip irrelevant blocks when filtering or aggregating by product_category. This directly reduces the amount of data scanned for the 30-day aggregation query, improving both performance and cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Cluster the table on product_category
Why this is correct
Clustering on product_category organizes data within each partition so that queries filtering/aggregating on that column scan fewer blocks.
- ✗
Change partitioning to monthly
Why it's wrong here
Monthly partitioning would include more data per partition, not reducing bytes scanned for a 30-day range.
- ✗
Denormalize the product_category into the sales table
Why it's wrong here
Denormalization doesn't reduce bytes scanned; it might even increase storage.
- ✗
Use a materialized view with aggregation on product_category
Why it's wrong here
Materialized views help but require maintenance and might not be as efficient as clustering for ad-hoc queries.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCDE exam.