Ten Recommendations for Simplified, Intelligence-Based Storage Management

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Reduce Storage Costs with Tiering and Archiving

Without good visibility and archival policies, companies put most of their data on high-performance systems, but this is a waste for infrequently used data. Analyzing the environment with regards to data types, usage patterns and performance needs can help to identify data that will live happily on slower, cheaper storage, and reserve the expensive capacity for data that truly needs it. Policy-driven storage management can set criteria for movement and execute the plan based on defined rules.

Data is the lifeblood of every organization, and as people and applications continue to generate more and more data, companies are struggling to keep up with capacity demand. This problem is felt most acutely with unstructured data – the fastest growing component of today's data center. To keep pace with and take advantage of the data, organizations are shifting to scale-out NAS architectures, object storage and advanced analytics that harness the power of Hadoop. But, to make this transformation a success requires automation and storage intelligence.

In this slideshow, Data Dynamics' CEO Piyush Mehta outlines 10 key recommendations for simplified, intelligence-based storage management.

 

Related Topics : Fujitsu, Storage Virtualization, Desktop Virtualization, Virtual Tape Library, InfiniBand

 
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