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

Artificial intelligence is the latest revolution in data insights everyone is talking about as organisations are increasingly looking to generate business value from their data. Only 4%* of organisations have successfully deployed AI, while most of the businesses are in the early phases of AI adoption facing unexpected challenges including access to data, scalability restrictions, a legacy IT infrastructure and a lack of specialist skills.

"Through 2020, 50% of enterprises will implement some form of data virtualization as one enterprise production option for data integration" according to Gartner. It is clear that data virtualization has become a driving force for companies to implement an agile, real-time and flexible enterprise data architecture.

Historically, reliably connecting all of the disparate sources of information across an organization was hard. You had to deploy, configure, and scale the middleware. There were queue policies to set and synchronization modes to understand. You also had to handle the transient nature of a message queue, ensuring the data reached

Migrating your IT assets from your corporate premises to the public cloud made sense—until it didn’t. Costs soared as businesses discovered storing and moving data had become cost centers, draining their operational expense budgets. Moving IT back on-premises poses a challenge to businesses whose facilities aren't typically considered data centers. Edge architecture is about designing and engineering components, chassis, and support structures to fit within unconventional locations. With Vertiv edge infrastructure, you’ll be moving your IT assets back on-premises, but this time they’ll be secure, manageable, responsive, adaptive, powerful, and out of your way.