Organisations are seeing exponential information growth in both, structured and unstructured data, and this is set to only grow manifold in the near future. The huge amount of data being accumulated on the internet has turned it into a mammoth animal. According to Andrew McAfee and Erik Brynjolfsson of Harvard Business Review, the 2.5 quintillion bytes of data generated by users on the internet every day is set to nearly double every 40 months. Already, there is more data passing through the internet every second than the entire data stored on it just 20 years ago.

This is the face of Big Data. How companies make use of this data gold mine is the determining factor behind whether they succeed or fail in today’s competitive business environment.

Sejun Ra

Sejun Ra, Founder, NFLabs

Everything is creating data – be it phones, sensors or internet devices. There is an imperative need to analyse this information to gain a competitive edge.

First, let us understand what Big Data comprises. This deluge of data goes way beyond the visible such as Facebook likes, tweets and website comments. Repeated, minute events generated automatically by devices could in fact turn out to be more important. Every click on a website, every signal packet sent by a smartphone is termed as ‘electronic breadcrumb’ – a data trail left by devices on the internet that savvy companies can analyse and exploit.

Take the example of the gaming industry that is increasingly making use of analytics to understand gamer habits and improve their products to boost the gaming experience. For instance, the levels at which users buy the most bonuses and which bonuses are the most popular, provide valuable feedback that can be used to refine difficulty levels. Also, for freemium games that rely on ad revenues, finding out how many gamers are online and at what time of the day goes a long way to better target their ads, providing more value to advertisers and hopefully increasing revenue.

Emergence of predictive analysis

We are seeing the rise of ‘predictive analysis’, where predictions about future trends and events are gleaned from analysis of current data. One particularly interesting example is the 2011 Egyptian Revolution, where careful analysis of Twitter data showed that a high correlation exists between hashtag frequency and various events of the revolution. A less political example would be Netflix, whose recommendations engine analyses consumer habits and predicts what they are most likely to watch next.

The more you understand customers, the more you will be able to aptly cater to their needs. No surprise that almost every company is turning to data analytics for better planning and informed decision-making.

Read also: Sparkline: Cutting through vanity metrics and finding the real data

Walking the talk
All this sounds fine in theory, but in practice many companies falter in their efforts due to the difficulty of data analysis, which require specialised skills that are not easy to find given the nascent nature of the field. Hadoop, the data processing framework for Big Data applications, is “powerful, yet slow and hard to use”.

Enter NFLabs and its product Peloton, a platform that packages Hadoop and adds a visual analytics environment, simplifying data analysis by presenting it in a graphical, easy-to-understand format. This allows data analysts to cut through Hadoop’s intricacies, making it easier to gain relevant insights.

The greatest market for NFLabs and Peloton is Asia. Unlike the United States and Europe, Asia is lagging behind in the adoption of data analytics. Many Asian companies have yet to implement data analytics to improve and grow their businesses. This is set to change due to the globalised nature of modern business, which will see Asian companies competing increasingly with more savvy Western firms. In a few more years, Asian companies will have no choice but to use analytics to gain a competitive advantage.

See also: It’s hard to define Big Data, but here’s how you can use it

South Korea, Japan, and Singapore stand out as particularly receptive to data analytics. All three countries share a relatively affluent and tech-savvy society, which leads to their relative speed in picking up new technology. In particular, Singapore has a huge need for data analytics, and Singaporean firms are looking at Hadoop to analyse data faster and more efficiently.

In the end, whoever can exploit analytics to the fullest will prevail in this new, data-driven economy. Future winners are going to be companies that can more effectively analyse the data they collect.

As told by Sejun Ra, Founder, NFLabs, in an exclusive conversation with e27’s Southeast Asia Correspondent, Terence Ng