Data Hub

Data driving skills demand

Big Data
Big Data has rapidly ascended as a major technique for every organisation to capitalise on the potential that sits within their data. FILE PHOTO | NMG 
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Google knows your health status, Facebook knows your appearance, while Netflix gives you recommendations with so much precision. Your local supermarkets probably know your shopping habits and it is no surprise that they target you with personalised vouchers and offers.

The future that analysts, technologist and science fiction authors predicted is here-we now live in a digital economy, where detailed consumer information is the new oil.

The mega rich of Silicon Valley, Google and Facebook are masters at harnessing collection, storage and analysing of data which we feed them every day. “The fourth industrial revolution and convergence of innovative technologies such as Big Data, Internet of things, cloud computing, geo-spatial data and broadband, Artificial Intelligence (AI) and machine learning, is promoting a dramatic shift towards more data and machine-driven societies, ” a 2018 Survey report by United Nations indicates.

Similarly, the modern computational power of analysing big data make it possible to use artificial intelligence to predict environmental changes.

For instance, Netflix has evolved over the past 20 years by focusing on its customers’ need to find movies they love. Headquartered in Silicon Valley, the company delivers digital content to any device and produces TV shows and films using data from its 130 million subscribers.

International Data Corporation (IDC) predicts that by 2025 the amount of data that consumers and businesses are creating will swell to a total of 163 zettabyttes (ZB), a ten-fold increase in today’s numbers.

The research also predicts that enterprises will take over consumers as the primary creators of data.

In the new digital economy, consumer data has become the biggest resource in any business and this has given birth to the current buzz of what they call “Big data’. But what is Big Data exactly and what made it bigger?

According to Gartner (2001), Big Data are high volume, high velocity and high variety information asset that require new forms of processing to enable enhanced decision making, insight discovery and process optimisation.

The idea that mass amounts of information can be analysed to find hidden patterns, buried beneath terabytes of numbers, in Facebook posts, Google searches and Amazon purchases. These patterns can predict social trends and, in some cases, reengineer the way we live.

For example, Alibaba is one of the best companies across all industries in its ability to extract the benefit from the roughly $450 billion in transactions it sees every year from more than 454 million shoppers. It combines external search engine and social media data with fully owned data from Alipay (payments), AntWealth (wealth management) and MyBank (financing) to inform which products to cross-sell customers on its retail site.

Companies have to determine how data can help deliver meaningful business improvements and what data (both internal and external) need to be collected to do so.

In the world we now live in, about 10 per cent of this Big data is structured, that is machine generated while 90 per cent is unstructured information, which is human generated information like emails, tweets, videos, Facebook post, call centre conversation and closed circuit TV footage.

This means consumers are largest data source. Successful businesses are giving a keener eye in mining invaluable information from their clients in order to customise their goods and services.

For this reason, Big Data is not just confined to the cluster of telco industries and the likes of Facebook and Google. Rather, it describes a particular way of acquiring and organising information that is increasingly indispensable to the economy as a whole.

Big Data has rapidly ascended as a major technique for every organisation to capitalise on the potential that sits within their data

Big data and AI can be exploited for better scenario planning and forecasting to improve resilience at all levels of society.

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