Edge Computing Market Size Set For Explosive Growth | Microsoft Corporation, NOKIA, IBM

Edge computing refers to the technologies that enable computation at the edge of the network, enhancing cloud computing systems. It involves processing downstream data closer to the end-user, providing low-latency solutions and self-executing decision-making capabilities. Edge computing facilitates data acquisition, handling, storage of high bandwidth content, and applications at the edge, leading to effective data management and cleaner data sets for cloud-based analytics.

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The market for edge computing is driven by factors such as the widespread usage of the Internet of Things (IoT) in industries, the demand for low-latency computing, and self-executing decision-making solutions.

Market Scope:

The analysis of the edge computing market covers the following aspects:

Components:

Hardware
Platform
Services

Applications:

Smart Cities
Location Services
Analytics
Environmental Monitoring
Optimized Local Content
Data Caching
Augmented Reality
Others

Organization Sizes:

Small and Medium-sized Enterprises (SMEs)
Large Enterprises

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Verticals:

Manufacturing
Healthcare
Transportation
Government
Media and Entertainment
Energy and Utilities
Telecom & IT
Retail
Others

Geography:

North America
Europe
Asia Pacific
Rest of the World

Component Analysis:

The market by component includes hardware, platform, and services. The hardware segment is expected to dominate the market in the forecast period due to the widespread adoption of hardware components for decentralizing storage and computing operations. Organizations are deploying edge infrastructure to reduce network traffic and enable comprehensive edge computing. Hardware components serve as data sources, facilitate network operations, and function as storage and local processing units within the edge computing process.

Application Analysis:

Among various applications, smart cities hold a significant market share. Smart cities leverage edge computing to enhance building security, automate home facilities, and improve traffic management to tackle congestion in metropolitan areas. Additionally, edge computing solutions enable optimized local content delivery, data caching, and augmented reality experiences.

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Organization Size Analysis:

Large enterprises drive the adoption of edge computing solutions due to their widespread geographic presence and the need for secure and efficient data storage. Increasing employee demands for access to computing solutions and applications from anywhere, along with secure data storage, further fuel the demand for edge computing solutions in large enterprises. For example, large manufacturing companies require access to abundant data from sensors or actuators connected to physical assets such as machines, turbines, and lifts, combined with historical information. This enables quick identification or prediction of failures to minimize production downtime and losses.

Geographical Analysis:

North America generates the highest revenue in the edge computing market. The integration of edge computing with the Industrial Internet of Things (IIoT) has led U.S. manufacturers to adopt connected factories. Additionally, the presence of startups offering edge-enabled solutions contributes to industry growth in this region.

Conclusion:

The global edge computing market is projected to grow at a CAGR of 37.5% from $4.04 billion in 2020 to $26.62 billion in 2026. Factors driving market growth include the increasing usage of IoT, demand for automated decision-making solutions, and the exponential growth of data. Key players in the edge computing market include Cisco, HPE, Huawei, Unit4, Dell Technologies, Microsoft Corporation, NOKIA, IBM, Foghorn Systems, and Machineshop. This analysis provides insights into market trends, opportunities, challenges, and the needs of end-users, assisting major competitors in understanding the market dynamics and evolving customer requirements. The report offers a comprehensive analysis of market drivers, opportunities, conflicts, challenges, and quantitative analysis across geographical regions.

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