While the term “Big Data” has been in common use for almost a decade, organisations are still struggling to deal with the concept as a more waves of information descend upon them in the age of connected supply chains, online customers and the Internet of Things.

Enterprises are well aware of the value in that data, says Ashutosh Bisht, Research Manager at IDC. “Big Data will be a game changer for enterprises and governments around APeJ. Enterprises across the region are adopting to Big Data and analytics for an added advantage, but most are yet to take off with full-scale implementation. And the vast majority are currently taking an ad hoc and opportunistic approach.”

Agreeing with Bisht is Marin Videnov, ‎Innovation Solution Advisor at SAP’s Platform & Database Centre of Excellence, who believes Big Data and AI are going to be driving a number of industries in the near term. “Big Data and AI represent a tremendous opportunity in the next three to five years in various sectors such as healthcare, transportation or manufacturing, to name a few. Think of the booming self-driving car industry, the exploration of the human genome or making our cities connected, sustainable and smart.

“Even without a data lake, every company I’ve met has already enough data to start extracting meaningful insights and get on the innovation journey straight away. What is often needed is not more data but a clear strategy, vision and courage.”

Intelligent enterprises effectively use their data assets to achieve their desired outcomes faster – and with less risk.

Big Data’s big impact

Big Data will have a big impact on many industries. Take banking as an example. Banking is going to look very different in five years, especially as financial institutions start applying AI to their data stores and real-time operations to drive down costs and enhance the customer experience.

Likewise mining, where the information generated by autonomous vehicles has allowed the companies to rethink their businesses — specifically in areas such as safety, productivity and cost reductions.

The rural sector also sees a big potential.

According to Tom Hansen, RuralCo CIO, “Our purpose is to be here for our farmers and support them in their businesses. One of our priorities is the use of analytics so that we can look ahead to predict outcomes for our customers and make an even greater impact for them.”

Hansen says the company wants to bring together data insights for its customers on weather, market conditions, soil conditions etc. and then use predictive analytics to show them what the best decisions would be at different times of year, based on this data and insights.

He also said analytics opened up new commercial possibiities as well.

“There is huge opportunity for data services and new technologies for companies like us and our customers and we are seeing pockets of great innovation across the sector.”

However, he said, the company is yet to see this at scale. “I believe this will increase rapidly as return on investment and impact is demonstrated through proofs of concept. Data already plays a pivotal role in the agriculture industry, particularly for our business, and this will continue to be fundamental in the future of farming.

A big challenge

Implementing a Big Data strategy is not without its challenges, as SAP’s Marin points out. “Despite the market infatuation and obvious real opportunities Big Data represents, a lot of companies have failed to implement Big Data projects.

“The pace of change is overwhelming to many. The ecosystem is evolving fast, especially in the open source world, and the increasing skill gap, combined with increasingly complex hybrid IT environments, is becoming a show-stopper for a majority of Big Data initiatives.

“This complexity shifts companies’ focus from the ‘why’ to the ’what is it’ and the ’how do we actually get there’, generating a disconnect between the business objective of a project and what was actually developed.

“I see a lot of Big Data projects ending as R&D-like exploration exercises. Only a few have been driven with a productive implementation in mind from start to finish. AI, in such a difficult context, is a distant dream to many, with most companies looking to solve more prominent problems — such as the access to the data itself.”

Part of the problem facing businesses, Marin says, is the volatility of data and companies not having a strategic view of where the information sits in the business. “I’ve heard this so many times, yet no quantity or variability of data is of any value if not analysed on time and on purpose.

“Accumulating information without having an understanding of why or how to use it is meaningless and costly. Not to mention that a very small percentage of such data is ever used. What’s more, as much as 60 per cent of that data loses its value within milliseconds.”

“What sets the most successful companies apart is their ability to steer and accelerate innovation by closely collaborating and co-innovating with a mix of technology, industry and business partners, thus continuously learning and adapting as the world around them changes.”

Intelligent enterprises effectively use their data assets to achieve their desired outcomes faster – and with less risk.

About The Author

Paul Wallbank is a Sydney based business writer. SAP is a is a corporate member of the Which-50 Digital Intelligence Unit. Our members provide their insights and expertise for the benefit of the Which-50 community. Membership fees apply.


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