FEATURE: BUSINESS ANALYTICS
and ensuring customer satisfaction) and
defensive (referring to data that helps
minimise risk, such as ensuring compliance
with regulations, maintaining the integrity of
financial reports and limiting fraud).
Offensive data activities require real-time
analytics to deliver the requisite business
insights and value to decision-makers.
An offensive data strategy aims to generate
customer and market insights, equipping
decision-makers with critical insights through
interactive dashboards.
Defensive data activities largely aim to
produce a ‘single source of truth’ by
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50% reporting directly to the CEO (up from
34% in 2016 and 40% in 2017).
Machine learning,
cloud enabling data
management success
Two key technologies are driving the
advancement of business analytics that
support real-time decision-making in 2018;
cloud and machine learning.
When organisations move their
transactional environment or business
systems into the cloud, it provides them
with two critical benefits; lower running
costs and standardisation.
TWO KEY TECHNOLOGIES ARE DRIVING
THE ADVANCEMENT OF BUSINESS
ANALYTICS THAT SUPPORT REAL-TIME
DECISION-MAKING IN 2018; CLOUD, AND
MACHINE LEARNING.
ensuring the integrity of data flowing
through the organisation.
Typically, defensive data management
strategies aim for control by optimising
data extraction, standardisation, storage
and access; offensive data management
strategies strive for flexibility by optimising
data analytics, modelling, visualisation,
transformation and enrichment.
An effective offensive data management
strategy requires the flexibility to produce
multiple versions of the truth to suit the
needs of different end-users by adding
relevance and purpose to data sets: for
example, weekly revenue figures that reflect
the key insights required by multiple lines
of business and can be adapted according
to the needs of each. This will prove critical
in 2018.
Forrester Research predicts that the majority
of Chief Data Officers will move from
defensive to offensive data strategies, with
40
INTELLIGENTCIO
A small team of expert data scientists
supported by machine learning algorithms
will enable organisations to leverage their
data to achieve positive business outcomes.
Machine learning can also help rank the
importance of data.
SAP’s Digital Boardroom, for example,
equips executive with real-time contextual
information and ad hoc analysis by
leveraging lines of business data from
multiple sources to provide a single source
of truth for the organisation.
Since the analytics layer queries directly
into the transactional or data warehouse,
decision-makers get real-time information
on actual business performance, with the
flexibility of presenting the information
in a variety of ways depending on
individual needs.
The disconnect between business analysts
and the business decision-makers they
support has been reduced significantly thanks
to the evolution of powerful cloud-based real-
time analytics platforms such as HANA.
Business leaders in 2018 need to start
the journey toward a cloud-based world
of actionable business insights leveraging
one of their most powerful – and often
underused – assets: data. n
Forrester Research predicts that half of all
enterprises will adopt a cloud-first approach
to big data analytics in 2018.
SAP’s HANA platform, for example, was
brought to market as a database but
quickly evolved into a platform that offers
organisations predefined data models,
predictive services, extractions into industry-
standard services, business analytics tools
and integration tools.
Today, SAP HANA can be deployed on
premise or in the cloud, helping to bridge the
gap between organisations’ historical data
analytics processes and the new world of
real-time predictive analytics.
Due to the escalating volume of data,
organisations are also increasingly turning to
machine learning to automate data analytics.
There is simply no way a business can
afford to employ an army of analysts to sift
through data to find value.
DUE TO THE
ESCALATING
VOLUME OF DATA,
ORGANISATIONS
ARE ALSO
INCREASINGLY
TURNING
TO MACHINE
LEARNING TO
AUTOMATE DATA
ANALYTICS.
www.intelligentcio.com