Many businesses are moving from data batch processing to streaming data. With the massive load of data, organisations receive from various sources every day, in multiple formats combined with complex business requirement has shown the world importance of streaming data.
With streaming data, you are offered a continuous stream of data. Which means no matter how many data sources you deal with, the technology allows you to process, store, analyse, and act upon data as they generate in real-time. This stream has no beginning or ending thus enabling you to use the feed without having to download first. Although data streaming is not new (gaming and media industry have been using the technology from decades ago) the technology is not only for live gaming experiences and live telecasts anymore as the modern business landscape has been demanding real-time data for a diversity of operations.
The technology ensures you a data flow as of a water stream without any discontinuations. Data streaming handles one data packet at a time. These pockets include their source and timestamp to ensure the applications to work seamlessly with data streams. It processes and analyses data in sequential order dealing with data just as they generated. The technology combines data coming from various sources, in different formats and sizes, at different speeds into a one continuous or combined stream.
Thus, whether its data received from applications, networking or IoT devices, servers, website activity, banking transactions or location data, the technology will gather everything in real-time to provide you with a unified source of truth. Not like in batch process where data is processed, stored and analysed in batches the streaming data ensure you up to the minute data.
Today many businesses across many industries embrace streaming data to meet the demand of the modern business requirements and users. Organisations are always pressured to optimise operational speed and production speed. Thus, technology solutions such as Cerexio real-time message broker is popular among organisations- As it enables different applications, systems, and services to exchange data and information and communicate with each other effectively. Such technological deployments are impossible without streaming data.
One of the top areas of expertise for deployment of streaming data for Cerexio is with our crowd analytics software which is widely used to understand customer behaviours and crowd behaviours in various industries. The solution analyses crowds in real-time with data from multiple sources. From HD cameras, live videos to sensors, the system use several data sources that generate data continuously. Further to ensure accuracy in analytics, streaming data plays a huge role with its smooth real-time data flow.
From gaming, manufacturing, pharmaceuticals, to mining and more many industries can take their operational capacity and the customer experience to the next level with streaming data. And Cerexio is here to help you find the best streaming data capabilities for your organisation.
At Cerexio, we have an experienced team who have worked with many organisations across many industries to help them make their shift from batch processing to streaming data smoothly. Regardless of the geographical boundaries and vendors (AWS, Azure, GCP, Private Cloud, etc.), Cerexio can stream the data in real-time using related technologies. For our clients, we always show the right technologies and tools for their requirements to ensure the highest possible ROI for their investment. Working closely with our clients, we focus our solutions on solving all your problems while exposing you the new possibilities that come with streaming data for your organisation. From the planning stage, deployment to scaling, we ensure you a smooth transition in your organisation, finding the best route to for minimum disturbance and effortless transformation.
Our track record in streaming data solution is second to none. Thus, we are looking for more companies to help embrace streaming data with our expertise.