The Networked Approach to Data Virtualization

zetaris
In this session, we go through the fundamental differences between operational data virtualization and analytical virtualization, while demonstrating the Zetaris’ Networked Data Platform approach, and the optionality it provides, as an essential part of any successful data strategy in today’s big data world.
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Spotlight

OTHER ON-DEMAND WEBINARS

Edge Computing Vs Cloud Computing

Simplelearn

Is the era of cloud computing coming to an end? experts predict that cloud computing is gradually making way for the next big thing: edge.nasscom product connect and simplilearn together present this live fireside chat on edge computing and how it stacks up against cloud. tune in to watch bernard golden, cloud computing expert and anand narayanan, chief product officer at simplilearn discuss this latest technology.
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Why Advanced Monitoring is Key for Healthy Enterprise Deployments

The use of Data Virtualization as a global delivery layer means that Denodo is a critical component of the data architecture. It cannot fail, needs to be fault tolerant and perform as designed. In this context, enterprise level-monitoring is key to make sure the virtual layer is in good health and proactively detect potential issues. Fortunately, Denodo provides a full suite of monitoring capabilities and integrates with leading monitoring tools like Splunk, Elastic and CloudWatch.
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Service Virtualization: Unlock the Power of Data Driven Virtual Services

Service Virtualization is a powerful testing tool that lets you simulate data and performance characteristics to mimic your APIs or other applications. Join Broadcom Software, Service Virtualization leaders - Andrew Gates and Beverly Mindle - as they share how data driven virtual services can simplify your environment and support your testing needs.
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Managing Data at Scale in VMware and Hybrid Cloud Environment

Rubrik

With more and more data being generated by organizations, it's increasingly important to manage and protect data at scale, across the edge, core data centers, and cloud environments. As applications and data are becoming more distributed a modern approach to data management is needed.
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