Which scenario best illustrates when to use a shared private parameter in a self-serve workflow?

Which scenario best illustrates when to use a shared private parameter in a self-serve workflow?

• A. You want the user to be able to choose the directory to write their data.
• B. You need the user to provide their own API key before running the workspace.
• C. You have multiple transformers with a Tolerance parameter, and you want them to use the same value and you don't want the end-user to set that value.
• D. You want the user to be able to choose the directory to write read data.

Answer: (C)

In a self-serve workflow you often need several transformers to rely on the same internal value, but you don’t want the end user to tweak that value. A shared private parameter provides a single source of truth for that value, shared across the transformers, while staying hidden from the user interface. Here, multiple transformers share a Tolerance setting, so using a single shared private parameter ensures they all use the exact same value and that you can change it in one place without exposing it to the end user. The other scenarios require the user to supply inputs like a directory or API key, which are public inputs and not suitable for a value that should remain internal and consistent across components.

In a self-serve workflow you often need several transformers to rely on the same internal value, but you don’t want the end user to tweak that value. A shared private parameter provides a single source of truth for that value, shared across the transformers, while staying hidden from the user interface. Here, multiple transformers share a Tolerance setting, so using a single shared private parameter ensures they all use the exact same value and that you can change it in one place without exposing it to the end user. The other scenarios require the user to supply inputs like a directory or API key, which are public inputs and not suitable for a value that should remain internal and consistent across components.