Legacy data migration is no longer fit for purpose, but what needs to change?
In a recent TechRadar article, product marketing professional Steve Leeper argues that legacy data migration is no longer effective in today’s complex IT environments. What used to be a simple “move the files” task has become far more challenging as organizations now juggle hybrid infrastructure and massive volumes of unstructured data—over 80% of what enterprises store.
According to Leeper, the core issue is that traditional migration tools treat all data equally. They can’t interpret context, value, or risk, which often leads to companies transferring stale, irrelevant, or sensitive data into the wrong storage environments. Instead of improving operations, legacy migration can create new inefficiencies and expose organizations to unnecessary risk.
Leeper says the fix starts with rethinking the entire process. Migration shouldn’t begin with moving data—it should begin with understanding it. Organizations need clarity on what they have, who owns it, how it’s used, and whether it still matters. Modern intelligent data management platforms make this possible through metadata analysis, automated classification, and policy-driven workflows.
With automation and analytics in place, migration becomes a strategic tool. Teams can align storage investments with data value, prioritize hot data for high-performance environments, and archive or delete cold data with confidence. This approach also supports stronger governance, streamlined cloud adoption, and cleaner long-term data landscapes.
Leeper notes that successful organizations treat migration as part of broader modernization efforts, not a one-off project. They track KPIs—cost reduction, compliance, accuracy, and accessibility—to improve future migrations and avoid disruption.
Ultimately, he concludes, modern migration is about creating adaptable, well-governed data ecosystems that evolve with the business—not just moving data from point A to point B.
