INTELLIGENT DATA CENTRES
In the case
of intuitive
networks built
on machine
learning,
algorithms
discover known
trends that
are prevalent
in data as it is
aggregated.
evolved from pattern recognition and
learning theory in artificial intelligence.
Networks with such inbuilt algorithms
can learn and make predictions from
data. With the help of these algorithms,
networks can overcome the limitation of
static programming and can make data-
driven predictions and decisions, through
building a model from data inputs. In
the past data mining has been used to
discover new trends in wide arrays of
collected data.
However, in the case of such intuitive
networks built on machine learning,
algorithms discover known trends that are
prevalent in data as it is aggregated.
Networks with in-built machine
learning and complex algorithms can
establish a pattern of baseline behavior
and can successfully flag deviations
without supervision. One of the immediate
benefits is the ability to successfully build
models of optimal network behavior and
proactively react without intervention to
anomalies and intrusions within.
Such new intuitive networks shift from
the traditional manual, time-intensive,
static mode of operation, towards one
that is capable of continuously learning
from the data that it manages for an
organisation. The more volume of data
it manages, the more it is capable of
learning through analytics and adapting
for automatic and efficient response. The
intuitive network automates the edge of
the network and embeds machine learning
and analytics at a foundational level.
Three fundamentals characterise these
innovative solutions. By enabling the
ability to move from manual operations
to automation, this network can scale to
manage millions of devices, establishing
its Intent.
By assessing data continuously in
context with the rest of the organisation,
the network can provide better insights
leading to proactive security actions
and efficiency. By virtue of the actions it
takes and assessment of the results, the
network can improve the results of its
future insights and also its future action,
hence Intuition.
Where does all this lead? The first is,
an intuitive network will gain the trust
of business and IT executives wanting
to select a platform to build their digital
business models of tomorrow. This will
be on the basis of its machine learning
capabilities, that it is constantly learning
and evolving to become highly secure and
provide insights.
And the second is, the intuitive network
is just the stepping stone to a much bigger
vision of creating intuitive technology
infrastructure. But for now, the network
remains the accelerator and enabler
towards this exciting end game.
An intuitive
network will
gain the trust
of business and
IT executives
wanting to
select a platform
to build their
digital business
models of
tomorrow.
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