Question 819 of 1,000
Ingesting and Processing the DatamediumMultiple SelectObjective-mapped

PDE Ingesting and Processing the Data Practice Question

This PDE practice question tests your understanding of ingesting and processing the data. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 is designing a batch processing pipeline that runs daily. The pipeline reads CSV files from GCS, transforms them using Python, and writes the results to BigQuery. They need to parameterize the pipeline for different environments and run it on a schedule. Which THREE components should they use? (Choose 3)

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

Cloud Composer

Cloud Composer (A) is correct because it is a managed Apache Airflow service that natively supports scheduling, parameterization, and orchestration of batch pipelines. It allows you to define DAGs that run daily, pass environment-specific parameters via Airflow variables or environment configurations, and trigger Python transforms or Dataflow jobs on a schedule.

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.

  • Cloud Composer

    Why this is correct

    Cloud Composer schedules and orchestrates the pipeline.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Dataproc

    Why it's wrong here

    Dataproc is for Spark/Hadoop, not Python-only transforms.

  • Dataflow Flex Template

    Why this is correct

    Flex Templates allow packaging Python transforms with runtime parameters for different environments.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Storage Transfer Service

    Why it's wrong here

    Storage Transfer Service is for file transfers, not processing.

  • Cloud Functions

    Why it's wrong here

    Cloud Functions are not ideal for scheduled, long-running batch pipelines.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the distinction between orchestration/scheduling services (Cloud Composer) and compute/processing services (Dataproc, Cloud Functions), leading candidates to mistakenly choose Dataproc for scheduling or Cloud Functions for batch processing.

Detailed technical explanation

How to think about this question

Cloud Composer uses Apache Airflow's DAG scheduler, which supports cron-based scheduling (e.g., @daily) and parameterization through Airflow variables, connections, and environment-specific configuration files. The pipeline can use Airflow operators like PythonOperator for transforms and BigQueryInsertJobOperator for writing results, while Dataflow Flex Templates (C) allow you to deploy containerized, parameterized Dataflow jobs that can be invoked from Airflow with runtime arguments, enabling environment-specific configurations without code changes.

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.

Related practice questions

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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: Cloud Composer — Cloud Composer (A) is correct because it is a managed Apache Airflow service that natively supports scheduling, parameterization, and orchestration of batch pipelines. It allows you to define DAGs that run daily, pass environment-specific parameters via Airflow variables or environment configurations, and trigger Python transforms or Dataflow jobs on a schedule.

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.