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Message: <blockquote data-quote="exam1passyq" data-source="post: 10755924" data-attributes="member: 325382">By "sharing nothing," new levels of availability, performance and scaling are achievable. GPFS-SNC is a distributed computing architecture in which each node is self-sufficient; tasks are then divided up between these independent computers and no one waits on the other.Created at IBM <a href="http://www.exam1pass.com/000-053-exam.html" target="_blank">000-053 </a>Research - Almaden, the new General Parallel File System-Shared Nothing Cluster (GPFS-SNC) architecture is designed to provide higher availability through advanced clustering technologies, dynamic file system management and advanced data replication techniques.With billions of files spread across multiple computing platforms and stored across the world, these mission-critical calculations require significant IT resource and cost because of their complexity.Using this GPFS-SNC design, running this complex analytics workload could become much more efficient, as the design provides a common file system and namespace across disparate computing platforms, streamlining the process and reducing disk space.IBM BERNARD CHAUS This web-based analytics tool supplied by Sky IT Group allows Bernard Chaus's suppliers and retailers to make production, order and markdown decisions based on real-time data from its own systems and its third-party retailers.In the case of Bernard Chaus, business analytics technology is helping the company swiftly respond to consumer demand, and improve margin performance by significantly reducing its quarterly sales revenue losses from marked down inventory by nearly 50% over the past year.IBM's <a href="http://www.exam1pass.com/000-053-exam.html" target="_blank">000-053 </a>current GPFS technology offering is the core technology for IBM's High Performance Computing Systems, IBM's Information Archive, IBM Scale-Out NAS (SONAS), and the IBM Smart Business Compute Cloud. These research lab innovations enable future expansion of those offerings to further tackle tough big data problems.</blockquote>

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