ENTERPRISE TECHNOLOGY
Savitha Bhaskar, COO Condo Protego.
transformation strategies that embrace
information management, with the
potential to add artificial intelligence and
machine learning for new insights,” added
Savitha Bhaskar.
IT infrastructure and operations
decision makers, frequently start their
bimodal IT infrastructure modernisation
efforts backward, by spending on new,
usually Mode 2 technology and talent
before properly assessing, rationalising
and simplifying their existing assets and
systems, which are often in Mode 1.
“In many cases, infrastructure and
operations decision makers can simplify
their infrastructure without significant
additional capital or operational
investment. This creates a stronger
platform to move forward and invest
wisely to position IT at the heart of
business growth,” says Phil Dawson,
Research Vice President at Gartner.
Through 2020, Gartner predicts that
80% of Mode 1 modernisation projects
will fall short of cost savings targets
due to a failure to simplify and address
unnecessary complexity. Moreover,
the extent to which Mode 1 projects
will effectively support new Mode 2
investments will often depend on how
well the process of simplification and
rationalisation has been carried out.
Elements of Gartner’s Mode 2, which
is also the convergence of cloud, storage
and compute, among others, is also going
through a significant transformation,
points out Mechelle Buys Du Plessis,
Managing Director, Dimension Data
UAE. “It has gone from on-premises to
moving originally into a hybrid kind of
architecture. And what we are seeing
now is hybrids and then moving fully
offsite into the cloud, but not just one
cloud. It could be a multiple number of
clouds depending on how the client would
like to have their workloads placed. Not
everything will live in the cloud. Some
stuff will continue to live on-premises and
that is fine. So, it is important to recognise
that,” she explains.
For channel partners it is important
to have a strategy that enables their
customers to move in this direction,
she stresses. “You have a strategy that
enables them to very quickly adapt, and
move, and be agile between what is on-
premises and what is in the cloud.” For
end users, the value is shifting a lot from
hardware to software in anything and
everything and Dimension Data has a
strong play there.
According to Mechelle, another area
where channel partners need to transform
themselves is in their ability, to take a
complex architecture design and articulate
that into business outcomes. “People often
have a challenge with that. A nice glue
between architects and the client is the
ability to transform that into a relevant
business case for the customer.”
A nice glue
between
architects and
the client is
the ability to
transform that
into a relevant
business case for
the customer.
Mechelle Buys Du Plessis, Managing Director,
Dimension Data UAE.
Phil Dawson, Research Vice President
at Gartner.
Advances in deep neural networks
have ignited a new wave of algorithms
and tools for data scientists to tap into
their data with Artificial Intelligence. With
improved algorithms, larger data sets, and
frameworks, data scientists are tackling
new use cases like autonomous driving
vehicles and natural language processing.
Data is the heart of modern deep
learning algorithms. Before training can
even begin, the hard problem is collecting
the labelled data that is crucial for training
an accurate AI model. Then, a full-scale
AI deployment must continuously collect,
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