What are the key privacy components of data mapping?

Learn all about key privacy components of data mapping and how to protect your information.
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Protecto
Leading Data Privacy Platform for AI Agent Builders
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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?
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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