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

  • Business Report
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Overview

Getting large-scale AI and analytics systems into production does not have to be as difficult as many people make it—the right unifying data infrastructure and a comprehensive data strategy let you scale without trading off performance or reliability.

This book contains over a dozen real world use cases plus practical advice on how to build scale-efficient systems ...

Getting large-scale AI and analytics systems into production does not have to be as difficult as many people make it—the right unifying data infrastructure and a comprehensive data strategy let you scale without trading off performance or reliability.

This book contains over a dozen real world use cases plus practical advice on how to build scale-efficient systems in a variety of industries, on-premises, at the edge, or in the cloud.

Discover how legacy applications can be combined with modern containerized Kubernetes workloads, all sharing the same data infrastructure.

Written by industry experts Ted Dunning and Ellen Friedman, this eBook shows why AI and analytics should run on the same system and explains how to get scalability without scaling IT resources.

Download courtesy of HPE.

O'Reilly report on recommendations for how to handle AI and analytics at scale while also keeping flexibility to increase scale and pivot to new applications or technologies as desired.