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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
respondido hace un año
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This does not explain why DataBrew decided my entire column should be null, nor does it really answer the question in any way.