Published on 2025-06-22T07:28:50Z

What is a Data Subject? Definition and Examples in Analytics

In analytics, a data subject refers to any individual whose personal data is collected, stored, or processed. Under privacy regulations like the GDPR and CCPA, data subjects have specific rights regarding their personal information, including the right to access, rectify, or erase their data. Analytics tools track interactions—such as page views, clicks, and user journeys—that originate from data subjects. While these tools aggregate and analyze data for insights, they must also respect data subject rights by implementing measures like anonymization, pseudonymization, and consent management. Solutions like PlainSignal provide cookie-free analytics that help protect data subjects and preserve privacy. Similarly, platforms such as Google Analytics 4 (GA4) incorporate features like IP anonymization and data retention controls. Understanding who the data subject is, and what rights they hold, is essential for compliance and ethical analytics practices.

Illustration of Data subject
Illustration of Data subject

Data subject

An individual whose personal data is collected or processed in analytics, entitled to rights under privacy laws like GDPR.

Understanding the Data Subject in Analytics

This section defines the concept of a data subject and explains its relevance in analytics processes.

  • Legal definition

    Under regulations like the GDPR, a data subject is any identified or identifiable natural person whose personal data is processed by an organization. This includes both direct identifiers (e.g., name, email) and indirect identifiers (e.g., IP address, device fingerprint).

  • Analytical context

    From an analytics perspective, the data subject is the source of behavioral data—such as page views, clicks, and navigation paths—used for deriving insights and optimizing user experiences.

Key Rights of the Data Subject

Privacy laws grant data subjects several core rights to control their personal information within analytics systems. Understanding and honoring these rights is critical for regulatory compliance and building user trust.

  • Core data subject rights

    Under laws like the GDPR and CCPA, data subjects possess multiple rights regarding their personal data.

    • Right of access

      The right to obtain confirmation and a copy of their personal data processed by the controller.

    • Right to rectification

      The right to have inaccurate personal data corrected without undue delay.

    • Right to erasure (right to be forgotten)

      The right to request deletion of personal data when there is no compelling reason to retain it.

    • Right to restrict processing

      The right to limit how organizations process their personal data.

    • Right to data portability

      The right to receive their personal data in a structured, commonly used format and transmit it to another controller.

    • Right to object

      The right to object to processing based on legitimate interests or direct marketing.

Implementation in Analytics Tools

Different analytics platforms have varying approaches to respecting data subject privacy. Below are examples of how two prominent tools handle data subject considerations.

  • Cookie-free analytics (PlainSignal)

    The following example demonstrates how to implement PlainSignal’s cookie-free tracking snippet:

    <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
<script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/plainsignal-min.js"></script>

    This approach respects the data subject’s privacy by avoiding cookies or persistent identifiers.

  • Google analytics 4 (GA4)

    GA4 uses pseudonymous identifiers and offers built-in data controls for consent management. It anonymizes IP addresses by default and enables data subjects to opt-out through consent banners or browser-level settings.

Best Practices for Respecting Data Subjects

Implementing privacy-focused strategies in analytics helps honor data subject rights and maintain compliance with global regulations.

  • Privacy best practices

    Adopt the following measures to ensure analytics processes respect data subject rights:

    • Obtain informed consent

      Use clear, unambiguous consent banners before any data collection.

    • Anonymize data

      Remove or hash personal identifiers to prevent tracing back to the data subject.

    • Provide opt-out options

      Offer easy-to-use mechanisms for data subjects to withdraw consent or opt-out of analytics.

    • Maintain transparent privacy policies

      Publish details about data collection, purposes, and data retention periods.

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