Lenovo & Nutanix Discuss HCI for SAP Landscape

This is a PowerPoint-style webinar to learn about the underlying infrastructure for running SAP deployments that can often be an after-thought or simply default to status quo. New technologies such as hyperconvergence and enterprise cloud should cause you to take another look. View this Americas SAP User Group webinar to learn about: The pros and cons of different infrastructure choices when considering the key building blocks for your SAP Business Suite and NetWeaver systems and Bridge to HANA, New options, like hyperconverged infrastructure from Lenovo and Nutanix.
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Spotlight

OTHER ON-DEMAND WEBINARS

5G From Theory to Practice - Lessons learned from the first 5G deployments

Infovista

Infovista's experts are supporting major 5G trials and deployments across the globe, working closely with Tier 1 mobile network operators and market-leading network vendors.In this exclusive webinar, they are sharing real-world insights and experience from deploying 5G networks to help you understand the key challenges and scenarios you can expect as you plan for 5G.
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Maximise the Impact of AI/ML with Enterprise Kubernetes

We’re witnessing an astonishing growth in the volume of information stored and processed in real time - now measured in zetabytes! As such, the world is well past the point where making sense of all this information is humanly possible and we need specialised tools such as AI/ML to reveal new intelligence and drive actionable outcomes.
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Artificial Intelligence in Procurement

Gartner

“The robots are coming and they’re going to take all of our jobs!” This is the fear people often have as we hear more and more about AI, or, artificial intelligence, in the workplace. And the fear is pervasive across just about every industry and job type, including blue and white collar jobs.
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How to Operationalize Machine Learning Projects

Machine Learning (ML) can empower a business and optimize its performance. However, according to Gartner, 85% of data science and machine learning projects fail. These projects aren’t delivering value because companies lack technical skills and have recurring issues with data infrastructure, deployment, and operationalization.
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