Storage Implications of Cognitive Computing

In the era of data explosion in Cloud-Mobile convergence and Internet of Things, traditional architectures and storage systems will not be sufficient to support the transition of enterprises to cognitive analytics. The ever increasing data rates and the demand to reduce time to insights will require an integrated approach to data ingest, processing and storage to reduce end-to-end latency, much higher throughput, much better resource utilization, simplified manageability, and considerably lower energy usage to handle highly diversified analytics. Yet next-generation storage systems must also be smart about data content and application context in order to further improve application performance and user experience. A new software-defined storage system architecture offers the ability to tackle such challenges. It features seamless end-to-end data service of scalable performance, intelligent manageability, high energy efficiency, and enhanced user experience.