Data plays a crucial role in the digital economy, and sharing it can open up new opportunities. For instance, businesses may collect customer details, including personal data, and use it to power better client experiences and marketing efforts.

Businesses collect data, like your name, location, and email address, which helps them market to you and new customers. Doing so, however, puts them at risk of data breaches.

To use data for business projects while complying with data protection laws like GDPR, companies may need to anonymize or pseudonymize personal data. So what do these two terms mean and what's the difference between them?

What’s Anonymous Data?

Anonymous data is information that cannot be traced back to a specific person, either by the organization processing it or another individual.

A person can be directly identified from data like their name, telephone number, and address. The goal of anonymizing data is to remove personal identifiers from data and make it impossible to identify a specific person from the rest of the data.

It also aims to make the process permanent. Data can only be regarded as anonymous if the re-identification of a person is impossible. This means that any party and those using known re-identification methods shouldn’t be able to find out who the data subject is.

What’s Pseudonymous Data?

Pseudonymous refers to using a name other than your actual legal name. For example, many authors, including J.K. Rowling, whose full real name is Joanne Kathleen Rowling, write under pen names like Robert Galbraith.

Pseudonymous data is personal information that has been altered such that the original data subject can’t be identified without adding extra details.

Anonymous and Pseudonymous Data According to GDPR

An illustration of GDPR

According to the General Data Protection Regulation (GDPR), anonymized data is data that has been altered in such a manner that it can’t be used to identify a specific person.

Because anonymous data doesn’t contain Personally Identifiable Information (PII), and the process is irreversible, it’s exempt from the GDPR. Keep in mind that data anonymization can destroy the value that data has for your company.

GDPR defines pseudonymous data as data that has been processed in such a way that it can’t be traced back to an identified or identifiable natural person without using additional information. This extra information is stored separately and is required to identify the data subject.

Since pseudonymous data can be identified, the GDPR considers it personal data.

How to Anonymize Data

Data anonymization is the action of removing any details that could be used to identify a specific person, so how can this be achieved?

Substitution

Substitution is the process of replacing specific data with a new identifier. For instance, you can replace sensitive information with an alternative identifier, such as “Participant-1,” in place of a person’s name.

Noise Addition

Noise Addition is often defined as obscuring data by adding or subtracting a small random number to a piece of numerical data, like weight. For example, you might round a person’s weight to the nearest multiple of five instead of reporting the exact figure.

Aggregation

Aggregation is grouping people who share components of their personal data while removing identifying traits. You can group people by region and not their exact places. For instance, you could use “West Coast” instead of the precise location “San Francisco.”

How to Pseudonymize Data

Lock and key illustrating encryption

For many companies, a lot of personal data goes through IT, marketing, and HR departments. Pseudonymization can help keep such data safe and prevent a possible data breach—all the while enabling its use for purposes like research and data analysis. Here are the common pseudonymization techniques.

Data Encryption

Data encryption alters personal data, making it unrecognizable without a decryption key, thus securing it. Decrypting the data for use will reverse it to its original form. Most of us use a form of encryption already, most notably passwords which should typically stored in a safe hashed or hashed-and-salted forms, rather than in plaintext (literally as it sounds: as plain, easily readable text).

Tokenization

This method protects data by substituting sensitive personal data with non-sensitive data, known as tokens. A token can be random numbers or a string of numbers used to identify a person without compromising their personal data.

Data Masking

Data masking is the process of substituting certain parts of personal information with a symbol or other placeholder, such as asterisks for your Social Security Number’s first four digits.

What Are the Benefits of Data Pseudonymization and Anonymization?

Data anonymization and pseudonymization are ways of protecting personal data while allowing data controllers to benefit from its utility. But what are the actual benefits of pseudonymizing and anonymizing data?

  1. Both anonymization and pseudonymization minimize the potential harm to data subjects that may result from data breaches. This helps data processors and controllers meet their data protection responsibilities.
  2. Anonymization safeguards the confidentiality of private data, minimizing questions and complaints regarding the disclosure of information obtained from personal information. You can also retain anonymized data indefinitely.
  3. Pseudonymization not only safeguards data but also helps companies comply with GDPR and similar data regulations. The technique can also be used on production systems to temporarily store original personal data during anonymization.
  4. If you show customers that you're responsible and complicant with data rulings, they will likely trust your business more, potentially resulting in repeat custom. A little trust goes a long way.

Achieve Data-Driven Growth While Maintaining Privacy

Companies today must take precautions to secure personal data and comply with privacy laws like the GDPR. To harness the power of data while protecting clients’ privacy, companies should anonymize or pseudonymize personal data.

Anonymized data is completely stripped of all identifying information, making it impossible to link the data back to a specific individual. Pseudonymous data has some identifying information removed, but it can still be linked back to a specific person.

To further protect personal data, companies should consider putting strong security measures into place, including carrying out regular risk assessments and audits, monitoring, and access controls.