FEATURE: DISRUPTIVE TECHNOLOGY
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To manage data at this staggering scale
and to efficiently find the data you need
from this massive tsunami of data, new data
management techniques are essential. Using
technology to transform the approach to data
management and overcome these obstacles
will leave businesses in a far better position
to successfully evolve. Two technologies
that have the capability to deliver massive
disruptive change in this area and across the
whole organisation are Artificial Intelligence
(AI) and Machine Learning (ML).
Krishna Subramanian, COO at Komprise
Businesses realise that leveraging data to
better understand and serve their customers
will make them more competitive. As a result,
companies are trying to become more data-
driven. But in order to accomplish this, they
need to be able to easily find and extract
relevant value from their data.
The challenge is that data footprint is
growing astronomically. According to
the analyst firm, IDC, the sum of the
world’s data – the DataSphere – will
grow from 33 zettabytes in 2018 to a
mind-boggling 175ZB by 2025. To put
this into perspective, one zettabyte is one
billion terabytes and an average desktop
computer has half a terabyte of storage.
So, this would be equivalent to 350 billion
desktop computers’ worth of data being
generated in 2025.
Nearly every industry that uses data has
a massive opportunity to be disrupted
by AI and ML. These technologies are
disruptive enablers because they have the
potential to transform technology that is
essentially low-level automation today, into
intelligent, learning systems. Therefore, the
big benefits of AI and ML are higher levels
of automation, simplicity and efficiency –
greater than what has been seen before.
the business value of AI will be about new
revenue possibilities’.
AI’s reliance on data is expected to
lead to significant transformation in the
data management industry. Adaptive
automation and Machine Learning will
enable data management software to
perform in smarter ways by observing
and leveraging patterns. AI-based data
management will start to be able to think
outside the box, offering more intelligent
ways to manage business needs.
Applying analytics and Machine Learning
will enable data management software
to observe the unique constraints of an
organisation’s environment and ‘learn’ to
work smarter by adapting its algorithms
This is supported by research firm, Gartner,
which predicted in 2018 that that business
value derived from AI would amount to
almost US$3.9 trillion by 2022, adding that
it ‘promises to be the most disruptive class
of technologies during the next 10 years
due to advances in computational power,
volume, velocity and variety of data, as well
as advances in deep neural networks’.
Gartner stated that customer experience
would be the primary source of derived
business value in the early years, but
new revenue will ‘become the dominant
source’ by 2021, ‘as companies uncover
business value in using AI to increase
sales of existing products and services, as
well as to discover opportunities for new
products and services. Thus, in the long run,
DATA IS THE LIFEBLOOD OF MOST
ORGANISATIONS AND BEING
ABLE TO TRANSFORM HOW THIS
INFORMATION IS MANAGED, STORED
AND COLLECTED WILL ALLOW THE
ORGANISATION TO INNOVATE.
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