In today's world, almost every one of us is playing a role in the proliferation of Fast Data. More and more real-time data is recorded with the onset of mobile devices, social media platforms and sensors. For enterprises, the ability to gain insights from such data as it is generated gives them a crucial edge.
Benefits of Fast Data
There are many examples of why Fast Data is becoming increasingly important in different industries. The telecom industry is a good example of that. A Fast Data approach can help telcos manage resources more effectively – it gives them the ability to gain insights as they occur, helps them understand allocation of network resources based on traffic and application requirements as well as network usage. This enables them to optimise capital expenditure (CAPEX) on network infrastructure while lowering or maintaining operational expenditure (OPEX).
The financial services industry is witnessing fierce competition. One of the most traditional styles of Fast Data in the financial services industry is using event correlation to contextualise available financial data. This can inform trading behaviour by identifying opportunities or threats that indicate whether traders (or automatic trading systems) should buy or sell.
Today, a wide variety of financial applications use event processing technologies, including profit, loss, and risk management systems, order and liquidity analysis, quantitative trading and signal generation systems, and others. The growing trend in this industry is to expand not only the use of event processing technologies but also real-time data integration and analytics. Data loses value at a faster rate and consequently the value that companies can get from data diminishes when it is not tapped into soon enough.
Fast Data is also highly applicable in the retail industry. Customer service centres are using Fast Data for click-stream analysis and customer experience management. Fast Data can factor real-time information about millions of events (clicks or other interactions) per second into business intelligence and other decision-support applications. These "recommendations" help customer service agents provide personalised service based on each customer's experience. Click-stream analysis can help target offers and even initiate customer service interactions.
These illustrations exemplify how Fast Data will slowly emerge as a key facet for organisations as they try to keep up with information from various sources to make real-time decisions. Companies are recognising the need to run their businesses in real time.
With Fast Data, businesses can improve efficiencies, develop higher quality in operations, build new services, and improve customer experience. Fast Data translates to faster business decisions and faster business actions. The time has come for organisations to start deriving benefits from their Big Data with Fast Data.
Chin Ying Loong is Vice President, Fusion Middleware, ASEAN, at Oracle.
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