Deploying the Edge for Real-Time Analytics

Data is said to be the new oil.  Data analytics is the future in technology industry. We have already learnt and experienced the power of the cloud and how it helps in our data storage, processing and management. The cloud does have a slight disadvantage when it comes to processing of data in real time. This is when edge computing comes to the rescue. Edge computing is very efficient for real-time analytics. We shall look at what really is edge computing and how it can be deployed for real time analytics.

What really is edge computing?

Edge- the word is defined by Gartner as the physical location where the people and things get connected with the networked digital world. Edge computing can be defined in simple words as the activity of processing your data near to the edge of your network, which is where the data is being generated rather than at the centralized data processing warehouse as being used in the earlier times. This essentially means that the edge devices do the computational work as opposed to the cloud environment.

The advantages of Edge Computing:

The main and most obvious advantage of edge computing is that it reduces the data transportation overhead. This means there is less volume of data to be moved, thus lesser traffic in the network and also less latency.

Edge computing also resolves the issues that occur due to the presence of a single point of failure which can affect the complete system. Edge computing is essentially computing using distributed nodes, thus even if a single node fails, the whole system can continue unaffected.

Things to keep in mind when deploying edge computing:

The first thing to keep in mind if you are thinking of implementing edge computing model in your business is the amount of data that you have. Data is the essence of this model. How much real time data processing capabilities will be required by your business is a factor to consider.

The cost factor: Cost factor varies as per the individual or business interests. Consider the trade-off between the cost of deploying edge computing versus the benefit you shall be obtaining from it. The return on investment and the time period is to be considered.

The connectivity of your organisation: A very stable internal network is required for the optimum functioning of the edge computing model. This does not necessarily mean that you must have a high bandwidth connection to the outside network, in fact you could minimise the connection to the outside network if you get the complete benefits of edge computing. A very good example of this would be the oil industry where systems are used to maintain the environmental condition in the operational centres and real time processing of data is very important.

These were few of the main factors to be considered when thinking of implementing edge computing in your organisation- The trade-off of the cost versus benefits, how much data do you have and how much real time processing you require and the connectivity in your facility

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BI Consultant

DataFactZ is a professional services company that provides consulting and implementation expertise to solve the complex data issues facing many organizations in the modern business environment. As a highly specialized system and data integration company, we are uniquely focused on solving complex data issues in the data warehousing and business intelligence markets.

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