What are the key privacy components of data mapping?

Learn all about key privacy components of data mapping and how to protect your information.

For instance, GDPR (article 30 and 36) requires organizations to document their processing and conduct periodic data protection impact assessments (DPIA). Without a comprehensive data map, organizations can’t comply with these requirements.

A comprehensive data map should have the following basic set of attributes:

  1. Data inventory – What data is collected?
  2. Storage – Where is the data stored? Is it secure and encrypted?
  3. Purpose – Why the data collected for?
  4. Use – Who has access to the data? Who is using the data?
  5. Flow – Where does the data flow? Who do we share outside the organization?
  6. Lifespan – When was it created? How long will data be stored? How will it be disposed of?
  7. Sensitive data  – What sensitive /personal data does the data source hold?
  8. Data lineage –  What data sources were combined or transformed to derive a data asset?
  9. Additional metadata that is relevant to data protection –
  10. What are the categories of data subject (customer, employee, partner, contractor) contained?
  11. What is the geographical location of data subjects in the data?
  12. Does it have a minor’s data?
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About the author

Protecto

Leading Data Privacy Platform for AI Agent Builders

Protecto is an AI Data Security & Privacy platform trusted by enterprises across healthcare and BFSI sectors. We help organizations detect, classify, and protect sensitive data in real-time AI workflows while maintaining regulatory compliance with DPDP, GDPR, HIPAA, and other frameworks. Founded in 2021, Protecto is headquartered in the US with operations across the US and India.

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Protect Sensitive Data Without Breaking AI Workflows
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Protect Sensitive Data Without Breaking AI Workflows

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