What process combines deidentified data sets with other data sources?

The process that combines deidentified data sets with other data sources is known as reidentification. Reidentification refers to the process of taking anonymized or deidentified data and correlating it with other information to reestablish the identities of individuals within that dataset. This is often done using additional data sources that contain identifying information, which can be linked back to the deidentified data to reveal the original identities.

This technique raises significant privacy concerns, as it can potentially expose individuals to risks if their information is reconstructed. In practice, organizations may need to take care to implement strong data protection measures to prevent unauthorized reidentification of the data.

The other options involve different data handling methods. Data masking refers to the process of obscuring specific data within a database to protect sensitive information. Aggregation and banding involve grouping data to lessen the granularity of the information, often for analysis or reporting purposes. Anonymization is the process of removing personally identifiable information from data sets, making it impossible to identify individuals. While important in data privacy and security, they do not directly involve the combination of deidentified data sets with other data sources in the way that reidentification does.