What action can be taken for records that do not match a regular expression?

The action to error out if records do not match a regular expression is particularly useful for maintaining data integrity. This approach allows for immediate feedback when data does not conform to expected patterns or formats, ensuring that only valid data is processed further. By implementing an error on non-matching records, you can promptly address issues such as data quality or formatting problems, which might otherwise lead to incorrect analyses or outcomes later in the workflow.

Skimming over records or logging warnings may allow for some flexibility, but these methods can result in carrying forward invalid records into downstream processes, which can be detrimental. Automatically correcting data without validation can introduce inaccuracies or unintended changes to the dataset, potentially leading to more significant issues. Therefore, causing an error when data doesn't match the specified regular expression is a proactive strategy that ensures the dataset remains high-quality and reliable for analysis.