The broad adoption of 5G, Internet of things (IoT) and edge computing will reshape the nature and role of enterprise and cloud storage over the next several years. What building blocks, capabilities and integration methods are needed to make this happen?

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In modern analytics deployments, latency is the fatal flaw that limits the efficacy of the overall system. Solutions move at the speed of decision, and microseconds could mean the difference between success and failure against competitive offerings. Artificial Intelligence, Machine Learning, and In-Memory Analytics solutions have significantly reduced latency, but the sheer volume of data and its potential broad distribution across the globe prevents a single analytics node from efficiently harvesting and processing data.

Have you ever wondered how intelligent Industry 4.0 factories or smart cities of the future will process massive amounts of sensor and machine data? What you may not expect is a digital twin will most likely play a role. A digital twin is a virtual representation of an object, system or process that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.