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Functional Separation — Protecting Big Data in a Privacy-Conscious World

Functional Separation — Protecting Big Data in a Privacy-Conscious World

This IDC Perspective outlines how organizations can process personal data using functional separation to avoid falling out of compliance with privacy regulations. Big Data projects involve multiple phases, including data collection, data integration, data analysis, and data distribution, during which protection of personal data must be considered for use within business processes. Both direct and indirect identifiers of customer, patient, employee, and other data subjects are handled differently depending on the use case. Organizations must continue to benefit from data assets, but must set in place the right solutions, processes, and training to safeguard privacy."Organizations must take appropriate steps to protect personal information to safely extract value from their data assets," said Dominic Trott, research director, European Security and Privacy. "Secondary usage of data beyond the purpose for which consent was initially obtained is a thorny issue where functional separation, sometimes called de-identification, can significantly reduce risks. This can enable organizations' Big Data projects to proceed while they protect privacy within the context of a growing list of international regulations."

Please Note: Extended description available upon request.


Executive Snapshot
Situation Overview
Advice for the Technology Buyer
Root of the Problem
Functional Separation: A Definition
Data Minimization and Privilege Management
Pseudonymization
Anonymization
Encryption
Privacy Protection Across the Phases of Big Data Projects
Create Oversight and Documentation
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Synopsis

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