centre of attention
‘The more
data a
business
has, the
smarter it
can become.’
• Taking remediation beyond error
codes to assign problems and
advise the appropriate team on
next steps.
• Learning application behaviour
and correlating it to the
underlying infrastructure’s
response. For example by setting,
behaviour-based thresholds.
• Ranking the relative impact
of each system issue, allowing
teams to troubleshoot in order
of most critical impact on the
user experience.
This technology is now finding
its way down from the most
cutting-edge enterprises in ways
that put it within reach of mid-
sized organisations, as well as
through leading APM and cloud
management platforms.
Predictive analytics for BI
requires a paradigm shift from a
reactive mindset to a strategic
one. This will mean a move from
managing day-to-day operations
to creating strategic initiatives, a
step that will ultimately generate
greater profit and revenue.
Get used to hearing
the term data science
as a service
analytics application, which are
typically the results users interact
with. However, the back-end
analytics are just as important.
Business analytics applications
actually increase the importance
of comprehensive monitoring
and ITOA, meaning that both the
front-end and back-end analytics
are used coherently. Here’s what
is ahead for both predictive
analytics and BI.
Make life easier
Real time ITOA will make jobs
easier for system admins and DBAs.
In the next few years, data analysis
and correlation will be required
to happen in real time. This ‘real
time ITOA’ means that Big Data
and analytics will perform changes
both supervised and unsupervised
– ITOA will make predictions and
fix issues before a problem gets out
of hand, without the input from
system admins and DBAs.
Here are a few ways ITOA on
the back-end can support analytics
initiatives on the front-end:
• Predicting future IT system states
and the impact of those states
on BI application performance –
such as when will your database
be out of space?
• Using the application stack’s
models, structures and patterns
to pinpoint previously unknown
root causes of overall system
performance issues.
Analytics is becoming increasingly
complex, which has led
organisations to look at how they
can deliver it in the form of Data
Science as a Service (DSaaS). DSaaS
gives organisations the ability to
utilise data analytics and predictive
mining in order to provide business
insights, without the need for data
scientists or other skilled analysts.
This brings ITOA to a new level ;
more of a strategic discipline.
The future of ITOA will involve
the management of real-time
infrastructures, with an environment
that has a mind of its own. By
harnessing the power of predictive
analytics, BI will drive better
performance across IT stacks, and
benefit the business as a whole.
August 2017 | 13