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Maintaining and Automating Data Workloads →mediumMultiple SelectObjective-mapped

PDE Maintaining and Automating Data Workloads Practice Question

You are building a data pipeline that ingests data from on-premises into Cloud Storage, then processes it with Dataproc, and finally loads into BigQuery. You need to schedule the pipeline to run daily. The pipeline must handle occasional failures gracefully. Which THREE Google Cloud services should you use together to achieve this? (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 Storage

Cloud Composer orchestrates the whole pipeline. Cloud Storage is the staging area. Dataproc processes data. BigQuery is the destination. Dataflow is not needed. Pub/Sub is for messaging, not scheduling.

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 Storage

    Why this is correct

    Storage is the landing zone for raw data.

  • ✓

    Dataproc

    Why this is correct

    Dataproc runs Spark/ Hadoop jobs for processing.

  • ✓

    Cloud Composer

    Why this is correct

    Composer schedules and orchestrates the daily pipeline with retries.

  • ✗

    Dataflow

    Why it's wrong here

    Dataflow is unnecessary; Dataproc is already used.

  • ✗

    Pub/Sub

    Why it's wrong here

    Pub/Sub is for event-driven ingestion, not needed for daily scheduling.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.