For enterprises that are planning for the digital transformation that will place data-driven workflows across all facets of business and commerce, I have bad news – the transformation is not coming but is already underway.
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On the PC, various hardware and software resources must function in harmony in order to produce something useful. This is why smart people invented the operating system.
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In the very near future, data infrastructure and architecture will need to be provisioned, tested, populated and integrated into the surrounding environment at a moment’s notice. And as the business office comes to realize the power this brings to their work processes, demand for this level of functionality will skyrocket.
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If you think you know what Big Data is going to be like based on the volume of today’s workflows, well, to coin a phrase, “you ain’t seen nothin’ yet.”
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It’s getting increasingly difficult to say where the data center, the cloud and mobile infrastructure separate. As workers become more adept at accessing data with their handheld devices, the enterprise is under the gun to ensure availability, portability, continuity and a number of other “ity’s” across distributed architectures.
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A lot of people are fretting over the Internet of Things and how it will affect enterprise infrastructure, particularly networks.
The specter of millions of data points sending continual streams back to the enterprise for capture, cleaning, analysis and downstream processing is enough to make any CIO cringe. It is also one of the reasons why so many organizations are looking to shore up their scalability and flexibility capabilities through virtualization and software defined networking (SDN).
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The enterprise is rapidly pursuing two key changes to data infrastructure in the drive to remain competitive in an increasingly digital economy. On the one hand, it is converting legacy network architectures into software-defined ones so as to build fully virtual data environments. On the other, it is undoing years of distributed physical infrastructure in favor of converged, modular footprints.
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The enterprise is eager to implement private and hybrid clouds even though full public infrastructure is likely to be less costly, more scalable and more flexible. At the same time, organizations are looking to supplement legacy virtual resources with advanced container platforms in support of broad service- and microservice-based data environments.
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Achieving data center efficiency is not only challenging on a technology level, but as a matter of perspective as well. With no clear definition of “efficient” to begin with, matters are only made worse by the lack of consensus as to how to even measure efficiency and place it into some kind of quantifiable construct.
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Everyone wants the latest, the greatest, the most cutting-edge technology. This is easy to do with a tablet or a smartphone but not when it’s an integrated enterprise data environment. In this circumstance, the only thing worse than falling behind the technological curve is throwing your processes out of whack with fork-lift upgrades.
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Enterprise Illumination 