Data Anonymization
Data Anonymization is the process of removing or modifying personally identifiable information from data sets in order to protect the privacy of individuals. This is done by replacing identifiable information with artificial identifiers or by removing certain fields altogether. The goal of data anonymization is to make it impossible to identify individuals from the data set, while still preserving the overall usefulness of the data for analysis and research purposes. Anonymized data is often used in situations where sensitive information is being shared, such as in medical research or in the analysis of financial data. However, it is important to note that complete anonymity is difficult to achieve, and there is always a risk of re-identification if the data is combined with other sources of information.
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