Question 411 of 1,000
Storing the DatahardMultiple SelectObjective-mapped

PDE Storing the Data Practice Question

This PDE practice question tests your understanding of storing the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A company uses BigQuery for analytics on petabyte-scale data. They want to improve query performance by denormalizing schemas and reducing joins. Which TWO BigQuery features should they use? (Choose 2)

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

Nested and repeated fields (ARRAY<STRUCT<...>>)

Option E is correct because BigQuery natively supports nested and repeated fields (ARRAY<STRUCT<...>>) to represent one-to-many relationships within a single row, enabling denormalized schemas that eliminate the need for expensive JOIN operations. This reduces data shuffling and improves query performance on petabyte-scale data by allowing all related data to be stored and scanned together.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Clustering on frequently filtered columns

    Why it's wrong here

    Clustering sorts data within partitions, improving query performance but not reducing joins.

  • Using subqueries instead of JOINs

    Why it's wrong here

    Subqueries can replace some joins but may not reduce complexity or improve performance as much as denormalization.

  • External tables reading from Cloud Storage

    Why it's wrong here

    External tables allow querying data in GCS, but do not affect denormalization.

  • Table partitioning by date

    Why it's wrong here

    Partitioning improves query performance by pruning partitions, but does not denormalize. It addresses different optimization.

  • Nested and repeated fields (ARRAY<STRUCT<...>>)

    Why this is correct

    These allow storing related data in a single row, reducing the need for joins.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the misconception that clustering or partitioning alone can replace denormalization, but these are physical optimizations that do not change the schema structure or eliminate the need for joins.

Detailed technical explanation

How to think about this question

Under the hood, BigQuery stores nested and repeated fields using a columnar format (Capacitor) that efficiently encodes repeated data as arrays, allowing queries to access nested fields without cross-table joins. In real-world scenarios, such as storing user events with multiple associated items, using ARRAY<STRUCT<...>> can reduce query time by over 50% compared to normalized schemas, as the data is co-located and scanned sequentially.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PDE question test?

Storing the Data — This question tests Storing the Data — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Nested and repeated fields (ARRAY<STRUCT<...>>) — Option E is correct because BigQuery natively supports nested and repeated fields (ARRAY<STRUCT<...>>) to represent one-to-many relationships within a single row, enabling denormalized schemas that eliminate the need for expensive JOIN operations. This reduces data shuffling and improves query performance on petabyte-scale data by allowing all related data to be stored and scanned together.

What should I do if I get this PDE question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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This PDE 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 PDE exam.