Unstructured data continues to grow exponentially. Analysts predict the growth rate of data in the enterprise to reach 650% by 2017, 80% of that being unstructured. At EMC Global Services, we’ve found some interesting factoids at our customers about this data. We’ve done hundreds of data analysis and classification projects, often as part of our data center consolidation projects.
What we’re finding is that most company’s unstructured data is in active use for only 30-60 days, and change is rare after 30 days. Data access is near zero after 180 days. Yet, this data is rarely managed or controlled, with users able to create sync and share, collaboration sites, or other repositories with limited justification to the IT department. Adding content to existing systems is free form. Because it’s not controlled or managed well, most companies have excessive duplication and incredibly inefficient use of resources. A lack of formal archiving solutions results in inactive data on primary storage, increasing storage management and backup costs. During our projects we discovered that as much as 85% of data on Tier 1 storage belongs on a lower class of storage. And applications aren’t running as quickly as they could if data was stored appropriately.
This is not an easy problem to fix – IT is charged with managing the data, but does not have a contextual understanding of it, or the authority to delete, archive, or determine its business value. Once the data is out there, it’s hard to get the users to clean it up. No one has time to go through their files and figure out if they want to keep them or not.
Solve this problem!
- Reduce costs by identifying and purging redundant and unused data
- Classify data based on its business value and consolidate to lower cost infrastructure
- Reclaim unused space to achieve higher utilization rates
- Eliminate unnecessary backups; move data to lower cost archival tiers
- Develop policies for continuously evaluating data
What will you get if you do? We’ve seen companies reclaim so much unused space that they avoided tens of millions of dollars in new CAPEX costs. Implementation of an archive policy can result in up to 60% reduction in primary storage usage with millions of dollars in primary and archival storage cost avoidance. Implementing a rules-driven data purge policy can reduce archival storage by 28%.
