What does data anonymization mean?
Data anonymization is the process in which identifiable information, like age, gender, name, etc., is changed or removed from a set of data so that it is impossible, or nearly impossible, to determine the individual the data belongs to. It is commonly referred to as “data sanitization” or “data masking.”
Any industry that relies on the collection of sensitive, personal information must practice some form of data anonymization. The level of anonymization varies depending on the nature of the business, the type of data collected, and whether the data is shared publicly or privately as a controlled release to a designated group of recipients. While certain elements of data must remain intact to provide value, data must be anonymized enough so that, if a breach does occur, the hackers cannot reap any benefits from the information. Properly anonymized data has no direct personal identifiers, such as names, addresses, social security numbers, or telephone numbers. It also contains no indirect identifiers, including place of work, salary, or diagnosis, that can be linked together to identify an individual.
Similar to anonymization, pseudonymization is used to protect sensitive, personally relevant information. Pseudonymization, however, does not remove all identifying information, but enough so that identifying an individual from what’s left would prove extremely difficult, if not impossible. Both anonymization and pseudonymization are important to GDPR regulations.
Common examples of data anonymization include:
- Medical research: Healthcare professionals and researchers looking to examine data pertaining to the prevalence of a particular disease among a specific population would perform data anonymization. This ensures they protect patients’ privacy and remain compliant with HIPPA standards.
- Marketing enhancements: Many online retailers want to improve how, and when, they communicate with their customers through emails, social media, digital advertisements, and their website. To improve their services and meet rising demand for custom or unique user experiences, digital agencies rely on insights gleaned from consumer data. To reap relevant information while remaining compliant, these marketers and analysts must leverage data anonymization.
- Software and product development: Developers often rely heavily on realistic data to develop new tools that can improve efficiencies, solve new challenges, and enhance service offerings. This data must be anonymized so that if a data breach does occur, highly personal information isn’t jeopardized.
- Business performance: Many large corporations gather employee-related data to optimize performance, increase productivity, and improve employee safety. Through data anonymization and aggregation, these companies can get the valuable information they need without making employees feel judged, monitored, or exploited.