AI and Analytics at Scale: Lessons from Real-World Production Systems

Presented by

Ted Dunning, CTO for HPE Ezmeral Data Fabric; Ellen Friedman, Principal Technologist for HPE Ezmeral

About this talk

Enterprises often make building large-scale analytics or AI / ML systems much harder than it needs to be. Rather than trying to build around limitations in their data infrastructure, there is another way. By using a scale-efficient system that adapts to change easily and in a cost-effective way⁠—scaling up or down, open to a wide variety of applications and tools, and with the ability to add new locations quickly⁠—organizations don't need to scale up IT resources. In this webinar, we will discuss: -How to tell if your system is scale-efficient -What steps you can take to improve scale-efficiency -How customers are taking advantage of scale-efficient data fabric

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Hewlett Packard Enterprise (HPE) is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.