Question 97 of 1,000
Ingesting and Processing the DataeasyMultiple SelectObjective-mapped

PDE Ingesting and Processing the Data Practice Question

This PDE practice question tests your understanding of ingesting and processing 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 data engineer needs to load data from CSV files in Cloud Storage into BigQuery. The CSV files have a header row and some columns contain nested JSON strings. Which TWO methods can they use to load this data into BigQuery?

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

Use the Storage Write API to write rows from a custom application

Option B is correct because the Storage Write API allows a custom application to stream data row-by-row into BigQuery, which can handle CSV files with nested JSON strings by parsing them in the application code before writing. This method supports complex data transformations and is suitable for real-time or near-real-time 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.

  • Use Datastream to load CSV files

    Why it's wrong here

    Datastream is for CDC from databases, not for file loading.

  • Use the Storage Write API to write rows from a custom application

    Why this is correct

    The Storage Write API can be used to stream data from CSV after parsing.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Create a federated query using an external table

    Why it's wrong here

    Federated queries read data directly from GCS without loading, but the question asks for loading.

  • Create a BigQuery load job with the CSV format

    Why this is correct

    BigQuery load jobs support CSV files with header rows.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use gsutil to copy files into BigQuery

    Why it's wrong here

    gsutil is for Cloud Storage, not for loading into BigQuery.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the distinction between loading data into BigQuery (permanent storage) versus querying external data sources (federated queries), causing candidates to mistakenly choose Option C as a valid loading method.

Detailed technical explanation

How to think about this question

The Storage Write API uses gRPC streaming to achieve high-throughput, low-latency writes, and it supports exactly-once semantics when configured correctly. For CSV files with nested JSON, the application must deserialize the JSON strings into BigQuery-compatible types (e.g., STRUCT or REPEATED fields) before writing, as the API does not automatically parse nested structures from raw CSV. In contrast, a BigQuery load job (Option D) can directly ingest CSV files and uses the 'autodetect' schema feature, but it may fail on nested JSON strings if the schema is not explicitly defined with RECORD types.

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.

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FAQ

Questions learners often ask

What does this PDE question test?

Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use the Storage Write API to write rows from a custom application — Option B is correct because the Storage Write API allows a custom application to stream data row-by-row into BigQuery, which can handle CSV files with nested JSON strings by parsing them in the application code before writing. This method supports complex data transformations and is suitable for real-time or near-real-time 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.