Data Retention & Expiration

Valuing All Data the Same?

Companies store many different types of information including email, file system data, personal, and collaboration data – some of which will also contain data for terminated or departed employees. While there are certainly business and regulatory reasons to maintain this data, significant portions commonly have a much lower overall value to the business

For those pieces of data this value commonly falls exponentially over time. With growth expectations showing no signs of slowing storing superfluous data on a platform with the same cost structure as high-value data does not make sense or provide an optimal total cost of ownership (TCO). In fact, storing all this data, and it's associated massive indexes makes finding quality or relevant data much more challenging.

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Struggling with Legacy Data during Transition?

In the midst of change, enterprise organizations often struggle with optimal strategies for handling legacy data. Some common scenarios where this is the case include retiring legacy applications and associated data, consolidating or exiting regional data centers, preparing for a merger or acquisition, preparing to leverage a new solution for compliance or eDiscovery, and implementing a new policy for individuals no longer with the company.

During these transitions, how and where data is stored will also need to undergo some change. With large organizations and hundreds of TBs or PBs of data, constantly moving massive datasets is no longer a viable option. The cost and time to do so often represents a negative return on investment (ROI) – which in turn complicates or forces abandonment of any go-forward planning.

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Expireon

Expireon enables enterprise organizations to manage legacy data during enterprise transformation projects. With a combination of long‐term retention and disposition capabilities along with data delivery on demand to desired eDiscovery targets, Expireon enables faster time to ROI when retiring legacy systems while expiring or transitioning data in the most cost‐efficient way possible.

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