An outcome of DCIG's research in SDS for file storage, the analyst evaluated 18 companies for a multi-site file collaboration solution use-case across 6 different categories. This report, available for free download, provides guidance on the DCIG TOP 5 solutions for providing effective file collaboration for distributed workforces.
Many organizations rely on effective file-based collaboration for core business processes. This worked well when employees sat in offices with fast links to file servers or NAS. However, today's modern workforce now spans the globe. When a dispersed workforce needs to work collaboratively on files using legacy systems, the result is frustration, lost time, lost money, and organizational risk.
Along with the change to a distributed workforce, organizations are integrating SDS solutions into their storage infrastructure for the increased flexibility, agility, and capabilities these software products offer. Many SDS-based file-storage solutions include features that enhance multi-site file collaboration and bring multiple benefits.
In the rapidly evolving landscape of artificial intelligence (AI), the underpinnings of data storage play a pivotal role in the success and efficiency of AI applications. As these systems become increasingly sophisticated, handling vast and growing volumes of data, the need for robust, scalable, and high-performance data storage solutions becomes paramount.
This article explores the essential data storage requirements for AI, shedding light on the critical factors that influence the design and implementation of storage systems capable of supporting complex AI workflows.
The importance of scalability as a data storage requirement for AI cannot be overstated, especially as AI applications become increasingly data-intensive and complex. Scalability ensures that a data storage system can handle growing amounts of data efficiently, without sacrificing performance or incurring prohibitive costs. This capability is critical for several reasons in the context of AI:
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