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Storing the Data →easyMultiple ChoiceObjective-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 wants to use BigQuery to query data stored in Parquet files in Cloud Storage without loading the data into BigQuery. Which BigQuery feature should they use?

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

✓

BigQuery external tables

BigQuery external tables allow querying data stored in Cloud Storage (including Parquet files) directly without loading it into BigQuery storage. This feature uses a federated query engine that reads the data on the fly, supporting formats like Parquet, Avro, ORC, CSV, and JSON. Option C is correct because it directly addresses the requirement to query Parquet files in Cloud Storage without ingestion.

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.

  • ✗

    BigQuery Omni

    Why it's wrong here

    BigQuery Omni is for querying data in other clouds, not for external tables on GCS.

  • ✗

    BigQuery ML

    Why it's wrong here

    BigQuery ML is for machine learning, not for external file querying.

  • ✓

    BigQuery external tables

    Why this is correct

    External tables allow querying data directly from GCS without loading into BigQuery storage.

    Related concept

    Read the scenario before looking for a memorised answer.

  • ✗

    BigQuery BI Engine

    Why it's wrong here

    BI Engine is an in-memory analysis engine, not for external file querying.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google often tests the distinction between features that query external data (external tables) versus features that process data within BigQuery (like BI Engine) or across clouds (Omni), leading candidates to confuse Omni's multi-cloud capability with external data access in the same cloud.

Detailed technical explanation

How to think about this question

When you create an external table pointing to Parquet files in Cloud Storage, BigQuery uses the BigQuery Storage API to read the files directly, leveraging columnar projection and predicate pushdown to minimize data scanned. Parquet's schema is automatically inferred, but you can also specify a schema explicitly. A subtle behavior is that external tables do not support DML operations (INSERT, UPDATE, DELETE) and have lower performance compared to native tables due to the lack of caching and indexing.

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: BigQuery external tables — BigQuery external tables allow querying data stored in Cloud Storage (including Parquet files) directly without loading it into BigQuery storage. This feature uses a federated query engine that reads the data on the fly, supporting formats like Parquet, Avro, ORC, CSV, and JSON. Option C is correct because it directly addresses the requirement to query Parquet files in Cloud Storage without ingestion.

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.