Back to all glossary articles

Data pseudonymization

In a nutshell, data pseudonymization is a method used to minimize the chance that personal data and identifiers would enable to identify a person.

Article 4(5) of GDPR states that:

‘pseudonymisation’ means the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person.

Benefits of using data pseudonymization:

  • You’re allowed to use it for the different purposes that it was collected for
  • You’re free from processing data subject requests regarding data access, rectification or erasure
  • You prove that you’re following protection by design and data privacy principles

Under GDPR, pseudonymization techniques are not enough to provide full anonymity of the data.

In terms of GDPR we can pseudonymise data like:

  • login details
  • device IDs
  • IP addresses
  • cookies
  • device type
  • language preference
  • time zones

Most popular methods of data pseudonymization:

Scrambling

Encryption

Masking

Tokenization

Data blurring

Read more about pseudonymization on the Piwik PRO blog:

  • HIPAA-compliant analytics for healthcare systems: How hospital marketing teams can measure what matters

    Patients now research symptoms, compare providers, and book appointments entirely online before ever contacting a hospital. Healthcare marketers need to adapt to digital-first patient journeys, run campaigns for numerous service lines, manage hospital marketing analytics across multiple locations, and prove ROI to administrators. For nonprofit hospitals, the picture is broader still — donation tracking is…

  • Privacy by design in practice: How “just enough” data beats “just in case” collection

    While collecting more data “just in case” feels safer, according to Matt Gershoff, it’s also one of the biggest sources of unnecessary compliance risk, analytical noise, and wasted organizational resources in the analytics industry today. His approach of “just enough” data collection is more intentional, more aligned with privacy regulation, and often more analytically effective.

Other definitions

Recent posts from Piwik PRO blog