Data Anonymisation What, How, and Why?
What
Data anonymisation is the process of transforming data so that it is no longer associated with an individual. This is important for protecting individuals’ privacy and complying with data protection regulations, such as GDPR, HIPAA, or CCPA.
There are a number of different techniques that can be used to anonymise data. Some of the most commonly used include:
- Generalisation: This involves making data less specific. For example, instead of recording a person’s exact age, you could record their age range.
- Suppression: This involves removing identifying information from the data altogether. For example, you could remove a person’s name, address, and postcode.
- Aggregation: This involves combining data from multiple individuals. For example, you could calculate the average age of all the people in a group.
- Pseudonymisation: This involves replacing identifying information with a pseudonym, or a fake name.
- Noise addition: This involves adding random data to the data. For example, you could add random numbers to people’s ages.
Why and How
There are a number of benefits to anonymising data. These include:
- Protecting privacy: Anonymising data can help to protect the privacy of individuals, avoiding data leaks, reputational damage, and substantial fines.
- Complying with regulations: Anonymising data will help organisations to comply with data protection regulations, as the ones mentioned above.
Here are some best practices for anonymising data:
- Consider the specific data: The best technique to use will depend on the specific data that you are anonymising, and the usage that you want to make of the data.
- Consider the level of privacy: The level of privacy that you need to achieve will also affect the best technique to use.
- Test the anonymisation: It is important to test the anonymisation to make sure that it is effective, and as accurate as promised by the supplier, using close to “real” examples – i.e. If your company manages data from customers based in France, take a sample of synthethic data from that specific country.
- Run it locally when possible: Data anonymization services – on the web or when using an API – involve the transmission and processing of data, even if it’s not retained. This distinction is important, as the original data owners might not have explicitly consented to this temporary access. Therefore, it is important to also evaluate solutions that run locally.
Conclusion
Data anonymisation is an important tool for protecting privacy. By following the best practices outlined in this post, you can help to ensure that your data is properly anonymised.
If you have any further questions, please do not hesitate to ask us by sending an email to support@embankai.com to learn more about our services for data and document anonymisation.
Elevate Your Data Protection
If you have any further questions, please do not hesitate to ask us by sending an email to support@embankai.com to learn more about our services for data and document anonymisation
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