Information Lifecycle Management
A comprehensive approach to managing data through all stages from creation to disposal based on its value and requirements.
Also known as: ILM, Data Lifecycle Management, Information Management Lifecycle
Category: Frameworks
Tags: data-management, storage, governance, organization, knowledge-management
Explanation
Information Lifecycle Management (ILM) is a strategy for administering storage systems and data throughout its lifecycle - from creation through final disposition. ILM recognizes that data value changes over time and manages it accordingly, optimizing storage costs while meeting access, compliance, and retention requirements.
**The information lifecycle stages**:
1. **Creation/Capture**: Data is generated or collected
- Focus: Proper classification, metadata capture, quality assurance
2. **Storage/Maintenance**: Active use and management
- Focus: Accessibility, integrity, security, performance
3. **Use/Access**: Data is actively referenced and modified
- Focus: Availability, search, collaboration, version control
4. **Archival**: Data moves to long-term storage
- Focus: Compliance, cost optimization, preservation
5. **Disposition**: Data is securely destroyed
- Focus: Compliance, security, verification
**ILM strategies**:
**Tiered storage**: Move data between storage tiers based on access patterns
- Hot tier: Fast, expensive storage for frequently accessed data
- Warm tier: Moderate performance for occasional access
- Cold tier: Slow, cheap storage for rarely accessed archives
**Policy-based automation**: Rules that automatically manage data movement
- Move files older than 90 days to archive
- Delete temporary files after 30 days
- Migrate completed projects to cold storage
**ILM in personal knowledge management**:
- **Capture inbox**: New notes start in a processing area
- **Active notes**: Working notes in easily accessible locations
- **Reference archive**: Stable notes for long-term reference
- **Project lifecycle**: Active → completed → archived
- **Regular reviews**: Periodic assessment of note relevance and value
**Benefits**:
- **Cost optimization**: Match storage cost to data value
- **Compliance**: Automated retention and disposal
- **Performance**: Keep active data on fast storage
- **Organization**: Clear expectations for data at each stage
**Challenges**:
- **Classification complexity**: Determining data value is difficult
- **Changing requirements**: Business needs and regulations evolve
- **Integration**: Tools and systems must support lifecycle policies
Effective ILM requires understanding that not all data is equal and that its value typically decreases over time - but not always linearly or predictably.
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