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PDE Maintaining and Automating Data Workloads Practice Question

An engineer needs to create a reusable Dataflow pipeline that can be executed with different parameters without modifying code. Which Dataflow feature should they use?

⚠ Common exam trap

PDE often tests the difference between Classic and Flex Templates, where candidates incorrectly choose Classic Templates for dynamic parameterization.

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

✓

Dataflow Flex Templates

Dataflow Flex Templates allow packaging a pipeline as a Docker image with a metadata file, enabling reuse with different parameters at runtime without code changes. They support dynamic parameters and are the recommended approach for reusable pipelines.

Answer analysis

Option-by-option breakdown

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

  • ✗

    Dataflow Shuffle

    Why it's wrong here

    Dataflow Shuffle is a backend execution service that moves shuffle data to the Dataflow service rather than worker disks; it exposes no parameterisation or reuse mechanism. It is tempting because it improves pipeline performance, but the requirement concerns passing runtime parameters without editing code, which Shuffle does not address.

  • ✓

    Dataflow Flex Templates

    Why this is correct

    Flex Templates package the pipeline as a Docker image with a metadata specification, so the same template runs repeatedly with different runtime parameters and no code changes. This satisfies the stem's reusability and parameterisation constraint.

  • ✗

    Dataflow SQL

    Why it's wrong here

    Dataflow SQL lets you author pipelines using SQL syntax over BigQuery datasets, but it does not itself provide a parameterised, reusable template invoked repeatedly with runtime values. It is tempting because SQL queries can contain variables, yet those are query parameters, not pipeline-level runtime parameters passed at job submission.

  • ✗

    Dataflow Classic Templates

    Why it's wrong here

    Classic Templates are legacy and cannot be flexibly parameterised at runtime without code changes; they are deprecated in favour of Flex Templates. It is tempting because templates package pipelines for reuse, but Flex Templates accept runtime parameters, which this scenario explicitly requires.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed September 2026 · checked against the official Google Cloud exam blueprint

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