Data Masking in Model Builder is particularly important for which reason?

Data Masking in Model Builder is particularly significant because it protects sensitive data during training. This practice ensures that any personally identifiable information or confidential data is rendered unusable or obscured while still retaining the utility of the data for building and testing models. This is crucial in today's data-driven environment, where compliance with regulations such as GDPR or HIPAA is paramount. By masking sensitive data, organizations can prevent unauthorized access to personal information while still leveraging the data's structure and relationships to train predictive models effectively. This approach helps maintain user privacy and safeguard sensitive information throughout the training process.