Description: Suppression is a method used in data anonymization that involves removing or obscuring specific data elements to prevent the identification of individuals. This process is fundamental in handling sensitive information, as it allows data to be used for analysis and studies without compromising the privacy of the individuals involved. Suppression can be applied to various types of data, such as names, addresses, identification numbers, and other personal identifiers. By removing or modifying these elements, the risk of the information being traced back to a specific person is reduced. This approach is especially relevant in contexts where large volumes of data are handled, such as in scientific research, market analysis, and demographic studies. Suppression not only helps comply with data protection regulations, such as GDPR in Europe, but also fosters public trust in the use of their data. However, it is important to balance suppression with the need to maintain the utility of the data, as excessive suppression can limit the ability to analyze and draw meaningful conclusions.
