t cht lk data infrastructure to meet new needs . As well , many storage solutions offer optimizations such as tiering which are proprietary to their filesystem . But if you want to switch vendors , you must rehydrate all the data and buy new high-performance storage from the vendor to move away from them . These downsides of single vendor solutions are why many organizations choose hybrid cloud and try to be storage independent . You need a data management solution that can right-place data across its lifecycle to higher performance storage such as GPU-ready storage or Flash storage and then tier it to cold storage such as the cloud when it is no longer accessed . IT teams want to leverage the best options across vendors .
t cht lk data infrastructure to meet new needs . As well , many storage solutions offer optimizations such as tiering which are proprietary to their filesystem . But if you want to switch vendors , you must rehydrate all the data and buy new high-performance storage from the vendor to move away from them . These downsides of single vendor solutions are why many organizations choose hybrid cloud and try to be storage independent . You need a data management solution that can right-place data across its lifecycle to higher performance storage such as GPU-ready storage or Flash storage and then tier it to cold storage such as the cloud when it is no longer accessed . IT teams want to leverage the best options across vendors .
What role does data fabric play in achieving unified data management across hybrid and multi-cloud ecosystems ?
You can create a data fabric with a data management solution that uses standard protocols to interface across a variety of storage and cloud options . This provides a unified way to analyze , mobilize and manage data workflows without imposing a filesystem or a proprietary namespace on the environment and delivers several advantages . You can use a variety of vendors for storage while still getting visibility across those silos and unified management without creating vendor lock-in . The storage-independent data management approach to a data fabric also has the advantage of bringing structure to unstructured data which is crucial for AI . Since unstructured data is often in petabytes , moving all the data to each AI solution becomes untenable as this could take months . Instead , a storage-independent data fabric provides a global index of all the data so you can search , curate and cull down exactly the right data you need for a particular AI task such as RAG and only move that data . It can also tag and retain the results of AI processing , so you do not have to repeatedly run the same AI workflow on the same data , which optimizes costs . p
Krishna Subramanian , Komprise Co-founder , President and COO
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