Automate data recovery


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Data classification
The food to fuel a policy manager and to set up and identify rules is information obtained via activity alerts, including event notifications from different sources. In some cases, different policy managers can signal or call on other policy managers to perform or invoke some function. Data classification can also help to identify data to apply policy rules. Classification tools, including traditional storage resource management (SRM) products, focus more on file, data path and access information. They collect and store meta data. Advanced data discovery, analysis and content classification tools, including those from Abrevity Inc., Index Engines Inc., Kazeon Systems Inc., Scentric Inc. and StoredIQ Corp., among others, can support BC and DR automation by helping you understand what data and information may exist in locations that you weren't aware of and thus not adequately protecting. The benefit of a deeper view into your data ensures that the data is being protected based on its content and context, and not just because of its file name or where it's stored.

Classified data can be used to support DR in one of two ways: passive and active. The passive method acts on the data after it has been stored; the active method applies policy rules to the data when it arrives for storage. An example of the passive approach is a virtual tape library that transparently creates a single-instance repository to compact and reduce

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the amount of data stored when creating a replicated copy for resiliency. An example of an active approach is when data is automatically replicated to multiple locations along with enforcing security, retention and other policy rules as the data is saved to a storage system. Data classification is also instrumental for a wide variety of storage functions, such as data archiving, data search and retrieval, migrating data to different tiers of storage and other information lifecycle management activities.

This was first published in August 2006

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