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Anonymizing unstructured data like medical records or legal documents is much harder than with structured data. The primary challenge is identifying sensitive information (PII) within free-form text, which can be obscured by jargon, abbreviations, and OCR errors. This guide explores the viable approaches, from simple rule-based systems to advanced Machine Learning and hybrid models.
An operational intelligence layer, the ontology, models relationships of entities and actions, enabling “digital twins” for organizations.
We’ve put together a simple guide on what we believe is a must have security functionality: anonymizing structured data effectively. Let’s ensure your data is both perfectly secure and fully usable for business operations.
Open-source solution unifying data and AI governance across platforms, from the perspective of a data intelligence engineer.