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Data Lifecycle Visualizer

Explore the journey of data from creation to destruction and track your data assets

Phase 1
Creation
Phase 2
Storage
Phase 3
Usage
Phase 4
Archival
Phase 5
Destruction

Data Creation

The beginning of the data lifecycle - when new data is generated or acquired

Key Activities

  • Data entry and capture
  • Document creation
  • System-generated data
  • Data import/acquisition
  • Sensor/IoT data collection

Security Considerations

  • Classify data at point of creation
  • Apply appropriate labels/tags
  • Define data owner and steward
  • Establish access controls immediately
  • Document data lineage

Compliance Requirements

  • GDPR: Consent for personal data
  • HIPAA: PHI identification
  • PCI-DSS: Cardholder data scope
  • SOX: Financial data controls

Data Storage

Where and how data is kept - critical for security and availability

Location Considerations

  • Geographic location (data sovereignty)
  • On-premises vs cloud storage
  • Primary and backup locations
  • Cross-border data transfer rules
  • Physical infrastructure security

Security Controls

  • Encryption at rest
  • Access control lists (ACLs)
  • Storage redundancy (RAID)
  • Backup encryption and protection
  • Physical security measures

Data States

  • At Rest: Stored on media
  • In Transit: Being transmitted
  • In Use: Being processed
  • Each state requires specific controls

Data Usage

Active processing and consumption of data for business purposes

Usage Types

  • Operational processing
  • Analytics and reporting
  • Decision making
  • Sharing with authorized parties
  • Machine learning training

Access Controls

  • Role-based access control (RBAC)
  • Principle of least privilege
  • Just-in-time access
  • Multi-factor authentication
  • Session management

Monitoring & Audit

  • Access logging
  • Activity monitoring
  • Data loss prevention (DLP)
  • User behavior analytics
  • Compliance audits

Data Archival

Long-term retention of data that is no longer actively used

Retention Drivers

  • Legal/regulatory requirements
  • Litigation hold obligations
  • Business continuity needs
  • Historical analysis value
  • Contractual obligations

Archive Storage

  • Cold storage solutions
  • Tape backup systems
  • Cloud archive tiers (Glacier)
  • Off-site secure storage
  • Write-once read-many (WORM)

Retention Policies

  • Define retention periods
  • Automated expiration rules
  • Legal hold exceptions
  • Periodic retention reviews
  • Document destruction schedules

Data Destruction

Secure, permanent removal of data per NIST SP 800-88 guidelines

Destruction Methods

Degaussing
Heavy magnetic field destroys data on magnetic media (HDDs, tapes)
Erasing
Delete operation - data potentially recoverable without overwrites
Clearing/Overwriting
Overwrite sensitive data with non-sensitive data
Purging
Multiple clearing passes + additional destruction methods
Disintegration
For SSDs - physical destruction via shredding/crushing
Incineration
Complete physical destruction by fire

Data Remanence

  • Residual data after erasure attempts
  • Magnetic media retains traces
  • SSD wear leveling complicates erasure
  • Forensic recovery possible
  • Verification required for sensitive data

Documentation Requirements

  • Certificate of destruction
  • Method used and verification
  • Date and responsible party
  • Serial numbers of destroyed media
  • Retain records per policy

Key Concepts

Data Location

Geographic location matters for privacy regulations. GDPR requires EU data to stay in EU or have adequate protections for transfers.

Data Maintenance

Ongoing checks to ensure data is accurate, complete, reliable, relevant, timely, and valid according to corporate standards.

Data Retention

Keeping data for compliance, litigation, business continuity, and historical analysis. Retention periods vary by data type and regulation.

Declassification

Process to purge media so it can be reused in unclassified environments. High-security environments destroy rather than declassify.

Data Asset Tracker

Track your data assets through their lifecycle phases

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