Data masking and anonymization techniques are employed to protect sensitive data while still allowing legitimate access for authorized users.
Data Masking: Data masking involves obscuring sensitive data within a dataset, replacing original values with fictitious but realistic substitutes. This technique ensures that sensitive information remains concealed from unauthorized users while preserving the overall structure and usability of the data.
Anonymization: Anonymization goes a step further by removing personally identifiable information (PII) from datasets entirely. It transforms data in a way that makes it impossible to associate individual identities with specific data records.
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