To protect consumer data from possible exposure, directives such as the General Data Protection Regulation (GDPR) mandate businesses to ensure privacy of their customers' personal information. In ...

Data anonymization is a broad subject. The permutations and combinations of methods that can be used to mask data are several, and they require expertise should you want to employ it properly.

Take advantage of the best synthetic data software for data anonymization and training AI models in 2023.

Specifically, data anonymization is the process of protecting private or sensitive information by erasing, encrypting, or masking identifiers that connect an individual to stored data. Examples of ...

Anonymization is the process of removing personally identifiable information from raw data, resulting in anonymized data that cannot be associated with any one individual.

Anonymization And Tokenization When dealing with sensitive data that can't be entirely removed, consider anonymization or tokenization techniques.

The Data Anonymization Tools Market grew from USD 83.22 billion in 2024 to USD 94.17 billion in 2025. It is expected to continue growing at a CAGR of 13.39%, reaching USD 176.97 billion by 2030.