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I understand that you will like to know the definition of valid and invalid in the context of Databrew.
The validity of a column in Databrew is based on the column type. For instance , if we have a column called HIRE_DATE with column type date:
- Valid in this context refers to the percentage of values with a valid date value
- Invalid refers to the percentage of values with an invalid date value
To replace the invalid values with select 'Invalid' and transformation and replace with desired options presented
répondu il y a un an
Contenus pertinents
- demandé il y a 2 mois
- demandé il y a un an
- demandé il y a un an
- AWS OFFICIELA mis à jour il y a 5 ans
This does not explain why DataBrew decided my entire column should be null, nor does it really answer the question in any way.