DATA LIFECYCLE01
Why do we manage data based on its birthday?
Age is easy to measure. Value, risk, retention, security, and future usefulness are what should determine lifecycle decisions.
INSIGHTS
Rethinking how enterprise
information is managed.
Perspectives on information lifecycle, Active Archive, optical storage, AI-era preservation, and long-term data strategy.
LATEST THINKING
Better questions lead
to better data strategy.
DATA LIFECYCLE02
Old data isn't necessarily cold data.
Information can become relevant again as business, regulatory, analytical, and AI requirements change.
DATA STRATEGY03
A file turning 90 days old isn't a business event.
Infrastructure-driven lifecycle rules often fail to reflect the actual business state of information.
OPTICAL STORAGE04
Why optical storage matters again in the AI era.
AI increases both the value and vulnerability of retained information, making durable and physically isolated preservation increasingly important.
ACTIVE ARCHIVE05
Performance and preservation should work together.
Important information should remain available on the right performance tier while being preserved on durable optical storage.
INFORMATION MANAGEMENT06
Technology changes. Information persists.
Applications, infrastructure, and media change. Information context, provenance, relationships, and governance must persist.
SAVARTUS PERSPECTIVE
Information should move
when its requirements change.
Not because a clock expired. Not because a file reached a certain age. Because the information itself changed.