Edge Computing refers to computing that is done as close to the source of the data as possible rather than relying on the cloud to do all the work. In other words, it is a distributed IT (Information Technology) paradigm that brings computation and storage of data around a network as near the source of data as possible. This doesn’t mean that the edge will replace the cloud, but rather extend it and bring it closer to you.

Read on to find out what edge computing is, how it works, how it differs from traditional IT and business computing as well as which are its benefits.

How data is handled. Today Vs the past
Data is at the core of modern business giving effective information while controlling important business processes and procedures in real- time. Nowadays, businesses are flooded with big amounts of data which can be collected from various loT devices and sensors operating remotely.

Edge computing architecture responds to any data challenges and traditional computing paradigms which were built on a centralised data centre. Slow internet connection, incapability to move continuously growing numbers of data, limitations around bandwidth, problems with latency or simply disruptions in the network are some of the factors that edge computing responds to compared to traditional paradigms.

How does Edge Computing work?
In simple words, edge computing takes a piece of data storage and other resources away from the main data centre towards the actual data source. Instead of processing and analysing data to a central data centre, edge computing performs the work where the data is originally generated, irrespective of its location.

The only thing that is transferred back to the main centre for review and other interactions is the result of the computing work done at the edge. This includes real-time business insights, maintenance of equipment and various calculations, predictions or actionable answers. As a result, edge computing is the new IT and business computing, or better yet, their new shape.

Edge Computing and trading
As we live in a fast-paced world of trading and decision-making, workstations should be able to perform very well to enable financial analysts to make the most of their devices in real-time analysis needs. Financial businesses, and scientist or analysts handling big amounts of data, need prediction-based outcomes and a way to reduce the cost of transferring data to the data centre or the cloud.

For example, people in the financial sector can use edge computing to create algorithms to assess the reliability of a client’s transaction in real-time. Edge computing can also help employees make their decisions faster and more accurate especially when it comes to underwriting and credit-scoring tasks.

In contrast to cloud computing, edge computing is becoming more and more valuable as it is used to analyse data in real-time fast and accurately, without bandwidth costs or latency issues. As Kirk Borne, Principal Data Scientist and Executive Advisor, Booz Allen Hamilton says, “The ability to do intelligence or knowledge discovery at the point of data collection is critical in many applications now,” says. “To manage fast moving data of all kinds of variety you need edge devices that are at the point of data collection – and are specific to the type of data collection – whether it’s imaging data or stream, like cyber network data, whatever is at the edge. You no longer have the luxury of bringing data back to your business centre and spending a year analysing it.”