Make Sure You Have The Right 'Edge' Over Competition
With more than a decade of experience in Business Advisor with a demonstrated history of working in the information technology and services industry, Srinivas is an expert in Hadoop, RPA, MSBI Power BI, Project Management and advanced MS Excel with Strong business and Analytical knowledge.
The most common question in the technology industry today is “What trends will shape the industry in the next five years?” The answer is applicable to every industry data and the ability to create a competitive edge from that data.
We live in the data era, characterized by an explosion of data sources and the race to collect data both from us and about us and innovations in analytics and artificial intelligence(AI)that help us extract more value from data. By 2025, most of this data will be processed outside a traditional data center or cloud. One of the hottest topics in this context is ‘edge’. Although there are many definitions of edge, I prefer a simple one that describes edge as any place where data is acted on near its point of creation to generate immediate, essential value.
The ultimate goal is to generate new business insights and move toward becoming a data-driven organization. Edge will be an important factor in making this happen. IDC predicts that by 2024, due to an explosion of edge data, 65% of the G2000 will embed edge-first data stewardship, security and network practices into data protection plans to integrate edge data into relevant processes.¹We anticipate that the entire data management ecosystem will develop and utilize edge IT capacity at the ingress and egress of their data pipelines and remotely process and digest data on the edge.
Edge solutions will become the most feasible option for realtime data processing and for harnessing data-driven insights at or near the source of data generation.This is very significant as it means a shift of focus on many fronts. Organizations will have to consider what data to capture at its edge locations such as branches for banks and stores for retailers. They will have to frame a seamless ecosystem with the right infrastructure to host the data, right place to run it, the right applications to analyze the data and, most importantly, the right process to manage and secure these remote edge locations.
The Retail Edge
In retail, the use of video analytics and computer vision has made it feasible to collect insights on customer behavior at the retail store level. This data, collected at the edge, can inform many departments within the retailer. Marketing can understand customer demographics in relation to the time of day, the weather or local events and deliver targeted content accordingly. Operations can use computer vision to detect unusual customer behavior and inform the store manager in real time. The customer experience department can analyze information on total store foot traffic, link it to actual sales and possibly change a store layout in response. Analyzing video data at the edge is key for these use cases because it’s not practical or cost effective to transport video data to a central location for analysis.
The Healthcare Edge
Healthcare is another vertical where edge use cases are gaining attention. Hospitals are looking for real time tracking of people and assets and combining it with other sources of data to generate meaningful insights. Advances in AI along with digital pathology are enabling pathologists to speed their image analysis, all while reducing human error. This analysis requires powerful GPU-enabled servers that are sitting at the edge, where the images are produced.
The Manufacturing Edge
In the manufacturing industry, where margins are tight and competition is fierce, many manufacturers are looking for ways to optimize their operations, minimize waste and create a better workforce experience. Data is leading them to deep operational insights driven by edge analytics. By collecting real-time data from programmable logic controllers (PLCs), edge analytics is enabling the monitoring of manufacturing process quality and providing early warning should something go wrong on the production line.
The Edge for Every Industry
Edge computing is one of the core components of the industrial Internet of Things and plays a significant role in accelerating the journey towards industry 4.0 adoption. As a result, modern data management is set to change. Most of the world’s data is predicted to move out of the public cloud environment where non-real-time, centralized data is being managed.Whatever industry one is in, edge will play a role today, and in the future, to drive efficiency and innovation through data. Hence, in this competitive landscape, to provide the best-in-class experience to their customers, organizations need to manage data effectively to extract maximum value from the edge to the cloud.
The most common question in the technology industry today is “What trends will shape the industry in the next five years?” The answer is applicable to every industry data and the ability to create a competitive edge from that data.
We live in the data era, characterized by an explosion of data sources and the race to collect data both from us and about us and innovations in analytics and artificial intelligence(AI)that help us extract more value from data. By 2025, most of this data will be processed outside a traditional data center or cloud. One of the hottest topics in this context is ‘edge’. Although there are many definitions of edge, I prefer a simple one that describes edge as any place where data is acted on near its point of creation to generate immediate, essential value.
The ultimate goal is to generate new business insights and move toward becoming a data-driven organization. Edge will be an important factor in making this happen. IDC predicts that by 2024, due to an explosion of edge data, 65% of the G2000 will embed edge-first data stewardship, security and network practices into data protection plans to integrate edge data into relevant processes.¹We anticipate that the entire data management ecosystem will develop and utilize edge IT capacity at the ingress and egress of their data pipelines and remotely process and digest data on the edge.
Organizations will have to consider what data to capture at its edge locations - such as branches for banks and stores for retailers
Edge solutions will become the most feasible option for realtime data processing and for harnessing data-driven insights at or near the source of data generation.This is very significant as it means a shift of focus on many fronts. Organizations will have to consider what data to capture at its edge locations such as branches for banks and stores for retailers. They will have to frame a seamless ecosystem with the right infrastructure to host the data, right place to run it, the right applications to analyze the data and, most importantly, the right process to manage and secure these remote edge locations.
The Retail Edge
In retail, the use of video analytics and computer vision has made it feasible to collect insights on customer behavior at the retail store level. This data, collected at the edge, can inform many departments within the retailer. Marketing can understand customer demographics in relation to the time of day, the weather or local events and deliver targeted content accordingly. Operations can use computer vision to detect unusual customer behavior and inform the store manager in real time. The customer experience department can analyze information on total store foot traffic, link it to actual sales and possibly change a store layout in response. Analyzing video data at the edge is key for these use cases because it’s not practical or cost effective to transport video data to a central location for analysis.
The Healthcare Edge
Healthcare is another vertical where edge use cases are gaining attention. Hospitals are looking for real time tracking of people and assets and combining it with other sources of data to generate meaningful insights. Advances in AI along with digital pathology are enabling pathologists to speed their image analysis, all while reducing human error. This analysis requires powerful GPU-enabled servers that are sitting at the edge, where the images are produced.
The Manufacturing Edge
In the manufacturing industry, where margins are tight and competition is fierce, many manufacturers are looking for ways to optimize their operations, minimize waste and create a better workforce experience. Data is leading them to deep operational insights driven by edge analytics. By collecting real-time data from programmable logic controllers (PLCs), edge analytics is enabling the monitoring of manufacturing process quality and providing early warning should something go wrong on the production line.
The Edge for Every Industry
Edge computing is one of the core components of the industrial Internet of Things and plays a significant role in accelerating the journey towards industry 4.0 adoption. As a result, modern data management is set to change. Most of the world’s data is predicted to move out of the public cloud environment where non-real-time, centralized data is being managed.Whatever industry one is in, edge will play a role today, and in the future, to drive efficiency and innovation through data. Hence, in this competitive landscape, to provide the best-in-class experience to their customers, organizations need to manage data effectively to extract maximum value from the edge to the cloud.
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