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Big data is a big opportunity for businesses, and its only getting bigger in Asia Pacific (APAC). According to market intelligence firm IDC, the global big data and analytics market is expected to grow to USD$203 billion; organisations in Asia Pacific that invest in big data, meanwhile, will reap an extra USD$65 billion in productivity benefits over less data-driven peers by 2020. IDC also reports that with 53% of organisations in the region believing that big data is important for business, it is undeniable that businesses must rely on data as a decision-making factor to enhance competitiveness.

Big Opportunity

The growth of the big data and analytics market is driven by growth of the digital transformation (DX) and Internet-of-Things (IoT) market in the APAC region. According to Future Ready Singapore, the number of connected IoT devices in Asia is expected to increase to 8.6 billion by 2020, up from 3.1 billion in 2015. IoT devices, like fitness trackers, smart TVs and the smartphones we carry contain networks of sensors that track and collect data.

This data can then be analysed to give actionable insights that both digital systems and decision-makers can act on to increase efficiencies or improve consumer experience. For example, advertising media collect data on customer surfing habits to better tailor advertisements offered to consumers.

New approaches to old problems

With this deluge of data, and the vast array of insights that remains to be mined from it, it’s natural for companies to seek data scientists on the payroll. These specialists use a range of tools from statistics to artificial intelligence to extract, clean up, and interpret meaning from data to give actionable insights businesses can act on. However, given the current and  predicted labour shortage in professional big data and analytics services, it is costly, especially for smaller companies, to hire data scientists.

Also read: How to build an in-house data science team (without a data scientist)

Trends with benefits

Instead of hiring someone to interpret data, it now is possible to enlist the help of software to do the same thing, but with greater speed and precision. This can be achieved via tools that harmonise massive and diverse data sets, transforming them into a knowledge base of intelligent insights. Let’s call it smart or intelligent data. This approach is not simply an alternative, but a primary choice for many companies.  Not only does it cut costs, it also lightens the burden on data scientists in having to extract, clean and transform data to make it usable. Data management and analytics software intuitively organise your data for ready use.

Here are just some sectors where big data and analytics can and is being applied to:

  • Banking and financial services – Gartner predicts that the banking and securities industries in APAC will spend USD$67.1 billion on IT in 2017, with a focus on advanced data and analytics tools. One of the largest applications of big data is in the financial industry to detect fraud. The sheer volume of transactions that financial institutions process daily is staggering, and of which only a small number might be fraudulent. Intelligent Data can help to surface discrepancies or anomalies in customer or employee behaviour that might indicate fraud, such as an excessive number of account access requests. It can also help to observe patterns and trends over time, and cross-reference various transactions to determine their authenticity.

Big Data for the Future

At the end of the day, businesses must consider investing in data technology, or risk being left behind. They operate in a world and in an economy that is overflowing with data, and there are plenty of relevant and strategic insights that can be derived from then.

By leveraging intelligent analytics platforms as an alternative to solely relying on hiring costly data specialists, businesses can empower every business user of theirs to make sound, data-driven decisions that ultimately aim to help their organisations benefit and prosper.


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