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Data is a valuable corporate asset, which is why many organizations have a strategy of never deleting any of it. Yet as data volumes continue to grow, keeping all data around can get very expensive. An estimated 30% of data stored by organizations is redundant, obsolete or trivial (ROT), while a study from Splunk found that 60% of organizations say that half or more of their data is dark — which means its value is unknown.
Some obsolete data may pose a risk as companies are dealing with the increasing threats of ransomware and cyberattacks; this data may be underprotected and valuable to hackers. Adding to that, internal policies or industry regulations may require that organizations delete data after a certain period – such as ex-employee data, financial data or PII data.
Another issue with storing large amounts of obsolete data is that it clutters file servers, draining productivity. A 2021 survey by Wakefield Research found that 54% of U.S. office professionals agreed that they spend more time searching for documents and files than responding to emails and messages.
Being responsible stewards of the enterprise IT budget means that every file must earn its keep down to the last byte. It also means that data should not be prematurely deleted if it has value. A responsible deletion strategy must be executed in stages: inactive cold data should consume less expensive storage and backup resources and when data becomes obsolete, there is a methodical way to confine and delete it. The question is — how to efficiently create a data deletion process which identifies, finds and deletes data in a systematic way?
Barriers to data deletion
Cultural: We are all data hoarders by nature and without some analytics to help us understand what data has truly become obsolete, it’s hard to change an organizational mindset of retaining all data forever. This unfortunately is no long …