A rapid , accurate response to our digital demands is what we as consumers now expect . Never has the need for speed been so acute , whether we are asking Alexa for today ’ s weather forecast , waiting for Prime Video to stream a movie , loading up a bank statement from our mobile account or checking out an online purchase . The longer we wait , the more likely we are to lose patience and abandon the transaction . It is no longer seconds that count , but milliseconds , and today ’ s businesses are built on their ability to respond in less than a blink of an eye .
This is what we term the ‘ Right Now Economy ’, and driving it is data which facilitates everything from daily tasks through to critical business actions . Every connection made by every device adds to the ‘ datasphere ’, as IDC has termed it . In its Global DataSphere Forecast for 2019 – 2023 , IDC predicts that there will be 55.9 billion connected devices by 2025 , generating 79.4ZB ( zettabytes ) of data from connected IoT devices alone .
No business , large or small , can disregard the immense economic and social shift driven by data . It is placing unprecedented pressure on companies to ramp up their real-time response , forcing them to move beyond human speed , instead entering the age of machine speed .
Once , organisations understood that if they couldn ’ t be first , they should be better . They prioritised agility so they could pivot quickly when trends changed . Now they urgently need to add the processing of large volumes of data from multiple sources into the mix , because only this will give them the real-time decisionmaking power to serve today ’ s right-now economics .
Let ’ s put this into context by examining three every-day scenarios : e-commerce , banking and gaming .
Fast shopping online
If a consumer is looking for a specific product , they might access a retailer ’ s mobile e-commerce app . Here they can search via recommendations based on a fast data layer and select the item they want . They can benefit from pricing that has been updated in realtime to reflect market demands and inventory that is up-to-the-minute accurate and pay for it in a matter of seconds . They are sent updates on the delivery in realtime , up to the point where the item arrives and , again , they are sent a real-time communication to complete the transaction . This process only works smoothly and accurately if it can access the customer ’ s data in realtime and that depends entirely on whether the retailer ’ s infrastructure is built for real-time business .
Facilitating safe money flow
In the financial services sector , the only way for companies to compete is by excelling at connecting and streamlining information flow across all data sources and datasets to meet customers ’ needs . This depends on capturing streaming data , preferably at the edge so it ’ s closest to where it ’ s needed , inputting robust AI and Machine Learning analysis and then pushing instructions and transactional outcomes back in real-time . This is how banks , insurance companies and payment service providers can rapidly authenticate digital identities , prevent fraudulent transactions without delay or inconvenience and provide customers instantly with the services they need .
Playing the game
In gaming , the need for real-time data processing is just as critical . Cloud gaming , PC and console-based gaming have long had appeal to consumers worldwide while emerging multi-player online games and eSports are attracting millions of gamers participating simultaneously against each other in real-time . This entails the storage , management and retrieval of massive volumes of player profile information , game performance data , statistics and rankings . Gamers rely on fast performance , low latency and high levels
Martin James , Vice President EMEA at Aerospike
The message for firms is clear : data architecture should enable and support , not restrict progress .
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