Photo: Chin Ying Loong.
Enterprises are constantly finding ways to differentiate, innovate, and radically transform their businesses. Today, most IT and business users are increasingly facing scenarios where they need better, cutting-edge information for business-critical decisions. In many cases, that information-led transformation is being enabled by Big Data.
It is of little surprise that Big Data is a widely discussed topic today. Without a doubt, the opportunities presented by processing these large, complex data sets are immense. We have seen developed economies make increasing use of data-intensive technologies to improve decision-making capabilities. For example, the Singapore government recently stated its aim to be a Big Data hub in Southeast Asia.
The fact is that Big Data is mostly focused on situations where data has already been collected and stored. And with vast amounts of real-time information created every millisecond, there is a need for a solution to manage the velocity of this Big Data, whilst acting on it with precision for real-time results. This is where Fast Data comes in.
Fast Data is the continuous access and processing of events and data in real-time for the purposes of gaining instant awareness and instant action. It is, in fact, a complementary approach to Big Data for managing large quantities of real-time data.
Fast Data can leverage Big Data sources, but also adds a real-time component of being able to take action on events and information before they even enter a Big Data system. By capturing data faster, it means businesses are able to analyse and act on it faster. For example by applying a Fast Data approach, an airline can better ensure that the right bags get loaded correctly, that flights leave the gate and take off on time, ultimately managing the airlines' operations in an intelligent, automated way.
Or allowing governments or city centres to use Fast Data to correlate and filter a vast number of events to support comprehensive real-time data collection and analysis for real-time intelligent traffic management, forensic analysis, vehicle journey history, traffic hotspots, crime density and so on.
As increased volumes of data become commonplace across many industry sectors, the value of applying a fast data strategy as an end-to-end solution will become more apparent. For instance, IDC's most recent Big Data technology and services market forecast shows that the worldwide Big Data technology and services market will grow at a compound annual growth rate (CAGR) of 31.7 percent—about seven times the rate of the overall information and communication technology market—with revenues reaching US$23.8 billion in 2016. Clearly, this is an indication that the volume, variety and consequently the velocity of data are on the rise.
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