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.
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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25 Aug 2006