We are done with the digital era! At least in referring to it as the next big thing in business. Truth of the matter is that digital transformation has been the talk of the town for five years running, and while its only in the last couple of years have we seen an open arms embrace of the idea, business models have been changing since businesses realized they cannot compete using traditional methods against the likes of Uber, Ant Financial, Softbank, and even Tencent.
Each of these companies have turned their industries upside down on the back of two core strategies: an almost maniacal willingness to experiment on the possibilities, and a relentless drive to acquire customer data and do something with it.
This last piece is important. Businesses like banks, insurance companies, telcos and utility companies have hoards of customer data. Their unwillingness to consider what is possible with this data, and to do something with it is what has stopped them from becoming the next Google or JD Finance or Grab.
The Accenture Technology Vision 2019 report says: “by transforming themselves to run on data, businesses have created a new kind of vulnerability: inaccurate, manipulated, and biased data that leads to corrupted business insights, and skewed decisions with a major impact on society.”
There is a challenge, however. Most organisations in Asia are still struggling to tame this data-volume explosion – let alone mining it for insight and business value.
To address this data-volume explosion, FutureCIO spoke to Mark Micallef, Cloudera vice president for Asia-Pacific and Japan, on what the industry has termed big data and how it is impacting businesses in Asia.
Describe the growth of Big Data in Asia.
Mark Micallef: There is indeed a strong appetite for big data growth in Asia. More and more enterprises are using data and analytics to fuel innovation or in fact, to accelerate innovation. There was a recent study done by IDC in fact that estimated the market size for this area will grow to about US$27 billion by 2022.
Also, Gartner had released a survey recently, talking to enterprise customers, which also is fuelling some of this growth around just the adoption of hybrid cloud and customers moving to hybrid architecture over time.
What is driving this growth?
Mark Micallef: I think if you take a macro level view first, any business theme, whether it’s 5G, which many telcos in the region are starting to pilot, you look at cashless economics, regulatory compliance, digital health care, also smart city initiatives.
All those things at a macro level are driving an increased use of data. But more importantly, increased use of analytics of data and governance of data. Those things at a macro level are driving the need for our platform or in these markets.
What is limiting growth?
Mark Micallef: It’s really three areas.
One – Customers are nervous about lock in. There was a recent study done by Harvard Business Review, and 1 in 8 customers, in fact, had slowed their adoption of public cloud for fear of lock in. And that’s one.
Skills is another area, obviously finding talent, attracting talent in the area of analytics, machine learning AI, that’s also a concern for customers.
And the third area I would say really is just wanting to ensure that technology that they adopt, which relates back to the first point, is around openness. The fear of vendor lock-in is not just a public cloud layer. It’s also at every layer of the stack.
Are organizations ready to embrace big data?
Mark Micallef: It comes back to the skills thing. And it’s around making the tools that we develop easier to use and therefore more pervasive in enterprise. That will make it easier for technology to be consumed. It makes it easier for customers to roll out new use cases as well. Coupled with the fact that public cloud now makes it easier to get access to compute.
So, we’ve hit an inflection point, if you think about it. And what’s happened is big data itself is nothing new as a problem or a challenge for enterprises as it’s been around for 10, 11 years – since the days of Yahoo.
What’s happened now is that the cost of computers come down. Accessibility to compute has become easier through the advent of public cloud.
What that means is that if I’m a data scientist, and I need to create a model, a machine learning model to automate the decision of a process or task, I can get to compute much more easily than I would ordinarily if it was on premise.
What are your top three recommendations for organizations considering Big Data strategy?
Mark Micallef: The first thing would be to have a very bold vision to think big, to be very aspirational about what data can do for enterprise. But to start small and to iterate often, transformation is not a short-term thing.
It’s not something that organizations can achieve and in a 12-month timeframe, and many of our customers are on journeys to deploy many use cases – 50, 60 use cases in production, that would be the first thing.
The second thing would be around embracing open. Embracing open means embracing open standards, embracing open source where a lot of the innovation is happening today. And by doing that, you are future proofing against decisions that you make today.
The third one is around the point that this is a transformation across the entire organization. It’s not a transformation for just IT, its transformation across the entire organization.
What does that mean? It means that the message around becoming data driven has to be top down, but also bottom up, it has to be embedded into the entire culture of the organization.
2020 is coming, how should enterprises prepare for big data?
Mark Micallef: 5G will enable applications that weren’t possible before, just because of the bandwidth capabilities, which will create an opportunity for a whole raft of new applications built around IoT, for example.
And so really, with that comes the opportunity to develop ways to ingest that kind of data that wasn’t possible before. And to ingest that data in a way that you can then apply things like analytics, but also going to go deeper than that to apply things like machine learning and AI to automate decisions that used to be done manually before. And so much of our growth in Asia Pacific is coming from Telecommunications Industry.
