Big Data is set to be one of the big growth areas in IT in the coming years according to research firm, Frost and Sullivan. One of the most innovative players in the space, Splunk, gave its top predictions for 2016.
Splunk country manager A/NZ, Simon Eid, said there were five main areas that would lead growth in the market in the coming year. Eid said the following:
Business leaders will demand better insights into how technology affects business goals.
In 2016, data science will be demystified more than ever, moving from Ph.D. to MBA. This means better and simpler ways to consume, analyse and correlate machine data from multiple sources.
This is like a domino effect we’ve seen unfold with many of our customers – just one example is the University of Adelaide. The University originally started using data analytics for identifying security threats but has since found many innovative ways of using data for insights, from monitoring Internet usage to even space planning.
As business leaders increasingly uncover opportunities new technologies bring to them, these digital insights will result in improved effectiveness, revenue, engagement and satisfaction among many other benefits.
The 'business operations centre’ will take form.
Traditionally, enterprises have taken a siloed approach of having an IT operations centre and security operations centre. However, in 2016 organisations can expect a huge push towards real-time business analytics, which will lead to the birth of the ‘business operations centre’.
This will be the greatest shift in business analytics next year, as enterprises realise they can no longer base their decisions on last month’s data. Instead, they now must run their operations in real time to address business issues as they arise.
The business operations centre will be mission-critical in enabling businesses to remain agile and providing crucial insights that impact the decisions of commercial leaders.
Machine learning will reduce time spent analysing and escalating events.
Today’s operations centres are challenged with an increasingly high volume of events that require human analysis. This volume will continue to grow and is unsustainable.
Machine learning has often been seen as an exploratory project or mere hype amongst the tech industry. But in 2016, we expect organisations to embrace machine learning for greater efficiencies that will significantly reduce the number of events requiring analysis down to the utmost critical.
Industrial IoT will fundamentally disrupt the asset intelligence industry.
According to the latest global figures from IDC, Internet of Things (IoT) spending is set to rise from $US698.6 billion in this year to almost $US1.3 trillion in 2019, with the Asia-Pacific region a clear leader globally.
By optimising organisations' understanding of the power that lies in their equipment and physical assets, industrial IoT will cut costs and create completely new revenue opportunities.
We are seeing examples of this beginning to emerge, such as at major retailer, Target. The company utilises machine data from robotic and automated systems at its distribution centres to improve its supply chain and influence business decisions.