While the past decade could arguably be considered an experimental phase in enterprise data analysis, most every organization now realizes the true value and competitive advantage it provides. As enterprise data analysis grows in importance, three paradigm shifts have begun to take place: 1.) The need to leverage AI and ML; 2.) Containerization discontinuity; and, 3.) The data explosion. Through it all, though, many organizations are challenged when it comes to data intensive applications, data storage environments, and AI/ML workflows.
Here to assist organizations in navigating through those paradigm shifts while boosting agility and openness is HPE Ezmeral, a platform already in place at some of the largest manufacturing, financial, healthcare, and retail organizations. Ezmeral is capable of meeting the immense challenges inherent within stateful workloads that demand enterprise-level speed, reliability, and scalability. Offering data fabric capability, Ezmeral further provides a unified view of your data while addressing the challenges posed by data diversity, degrees of scale, reliability, resiliency, and the need to view a globally distributed set of data. Because Ezmeral is agnostic, it’s also able to run within any cloud or hardware environment.
HPE’s Ezmeral gives organizations more control over their data along with a myriad of apps and microservices in containers. With ML Ops capabilities, you also gain DevOps-level agility throughout the entire machine learning lifecycle—notably enhancing collaboration. Learn more at: https://community.hpe.com/t5/HPE-Ezmeral-Uncut/How-HPE-Ezmeral-is-helping-organizations-conquer-today-s-data/ba-p/7114605#.YCGu2S1h1QI.