Terms like ‘sensitive data’ and ‘personal data’ have been floating in the air ever since GDPR, CCPA, and similar privacy acts were introduced to companies across the globe. One challenge they present is that the complexity of the federal laws and complicated terminology used to identify the corresponding subjects make it difficult for those in the technical field to truly grasp.
It becomes harder than ever for the data scientists to figure out the main challenges of processing datasets containing sensitive information and how the data should be anonymized properly.
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