If the IT executive takes anything into the new year, it should be the knowledge that data is no longer the means to conduct business, it is the business.
For far too long, the biggest problem for the enterprise has been the disjointed, silo-laden infrastructure underlying its data-driven processes.
For IT executives already feeling the pressure to implement digital transformation across the enterprise, here is some bad news: Expect things to get even worse in the years to come.
Of all the changes coming to the data center, perhaps none is as futuristic as autonomy.
While storage is crucial for analytics, the enterprise should take care not to develop storage infrastructure in isolation from the rest of the data environment.
To say that blockchain has the potential to be disruptive is probably the understatement of the year.
Micro data centers represent a fundamental shift in the way the world interacts with data, and we have yet to gauge the impact that this change will have on our digital lives.
As with most technology developments, the initial view surrounding the SDDC is how it will improve current data operations.
The most efficient use of resources will always be dependent on sometimes highly subjective expectations as to the best way of achieving a goal.
It seems that the data center industry is still feeling its way through the conversion from hardware-centric to software-centric infrastructure, leaving open the possibility that no single architecture will dominate the future.
Some leading experts are saying that container technology is so revolutionary that it threatens to supplant the operating system as the linchpin of the data stack.
The purpose behind IT technology development is to make work processes simpler and the knowledge worker more efficient. But the workforce is frustrated with the tools it uses.
AI will foster a world in which computing expertise is no longer a prerequisite for building and deploying applications and services.
Even the most advanced AI platform can only produce results that are as good as the data it is given and according to the parameters in which that data is queried.
In terms of application importance, the private cloud is likely to support the heart of data operations for some time to come.
When inevitable outages occur, and surveys indicate this should happen less frequently in the cloud than on traditional infrastructure, the enterprise is still responsible for maintaining IT services.
Artificial intelligence is going to arrive within the next few hardware refresh cycles now that vendors of all stripes are building it into their core platforms.
It turns out that the biggest hurdle blocking digital transformation is how to manage all of the unstructured data that these fast-moving applications are expected to generate.
Before enterprise executives decide on what type of the cloud they are going for, it might help to determine what types of apps need to be supported and how they can best be applied to operational and business objectives.
Increasingly commoditized, hyperconverged infrastructure is cheaper to deploy, easier to maintain, and capable of providing the resource flexibility required of next-generation apps and services.
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