FEATURE: BIG DATA
In 2019, it’s estimated we’ll
generate more data than we did in
the previous 5,000 years and it is
fast becoming the most valuable
asset of any modern organisation.
However, while most have access
to their internal data, they continue
to experience challenges in deriving
maximum value. Zakes Socikwa,
Cloud Big Data and Analytics Lead
at Oracle, tells us more.
T
he foundation of any analytics or Business
Intelligence (BI) reporting capability is an
efficient data collection system that ensures
events or transactions are properly recorded, captured,
processed and stored. Some of this information on its
own might not provide any valuable insights, but if it
is analysed together with other sources might yield
interesting patterns.
Big Data opens up possibilities of enhancing internal
sources with unstructured data and information from
Internet of Things (IoT) devices. Furthermore, as we
move to a digital age, more businesses are implementing
customer experience solutions and there is a growing
need for them to improve their service and personalise
customer engagements.
The digital behaviour of customers, such as social media
postings and the networks or platforms they engage with,
further provides valuable information for data collection.
Information gathering methods are being expanded to
accommodate all types and formats of data, including
images and videos.
In the past, BI and Data Mining were left to highly
technical and analytical individuals, but the introduction
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of data visualisation tools is democratising the analytics
world. However, business users and report consumers
often do not have a clear understanding of what they
need or what is possible.
AI now embedded into day to
day applications
To this end, Artificial Intelligence (AI) is finishing
what business intelligence started. By gathering,
contextualising, understanding and acting on huge
quantities of data, AI has given rise to a new breed of
applications – one that’s continuously improving and
adapting to the conditions around it. The more data that
is available for the analysis, the better is the quality of
the outcomes or predictions.
In addition, AI changes the productivity equation for
many jobs by automating activities and adapting
current jobs to solve more complex and time-consuming
problems, from recruiters being able to source better
candidates faster to financial analysts eliminating manual
error-prone reporting.
This type of automation will not replace all jobs but will
invent new ones. This enables businesses to reduce the
time to complete tasks and the costs of maintenance
and will lead to the creation of higher-value jobs and
new engagement models. Oracle predicts that by
2025, the productivity gains delivered by AI, emerging
technologies and augmented experiences could double
compared to today’s operations.
According to the IDC, worldwide revenues for Big Data
and Business Analytics solutions was expected to total
US$166 billion in 2018, and forecast to reach US$260
billion in 2022, with a compound annual growth rate
of 11.9% over the 2017 to 2022 forecast period. It
adds that two of the fastest growing BDA technology
categories will be Cognitive or AI Software Platforms
(36.5% CAGR) and Non-relational Analytic Data
Stores (30.3% CAGR).
Why AI and Machine
Learning are vital
to tackling the data
explosion
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