That idea ties back into the topics of data growth, data control,
data management and recoverability. Once you start categorizing
your data based on criticality and
recovery priority, it gives you an
indication of your data segments. We have our high-priority
data, we have our medium criticality data and we have our low
restore priority data. This is a perfect opportunity, if you're
looking into doing
tiered storage, to start dividing your data
or using those categories to store your data.
@24733 From a cost perspective, if your data is highly critical
to your organization and you want to replicate it because it's so
critical you can't afford downtime -- that data probably belongs on
your highest-performance, most redundant storage
array. Conversely, if you have data that can
wait because there's really no rush to restore it, then maybe
that belongs on your lowest tier or your lowest cost storage --
or even potentially
archived on tape. Tiered storage can
complement DR efficiency, ensuring that the most critical data
is recovered first.
Information lifecycle management (ILM) ties
right back into all of this. ILM, or data lifecycle management,
is all about categorizing the data based on its criticality or
potentially some legal requirements, but again ties very closely
into tiered storage or data tiers. Do you keep your less
valuable data on your top tier? Probably not. If the data is
reaching the end of its lifecycle it should probably be moved to
a storage media of lesser cost and lesser performance because at
this point we're just keeping it for potentially legal reasons.
Tying back into disaster recovery, we're probably not going to
restore that less valuable data immediately following a
disaster. All of this information can help you classify data
based on criticality, value to the organization or legal
implications.
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