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市场调查报告书
商品编码
1691790

零售边缘运算市场 - 全球产业规模、份额、趋势、机会和预测，按组件、按应用、按组织规模、按地区和竞争进行细分，2020-2030 年预测

Retail Edge Computing Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Application, By Organization Size, By Region & Competition, 2020-2030F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3个工作天内

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简介目录

2024 年全球零售边缘运算市场价值为 48.7 亿美元，预计到 2030 年将达到 151.9 亿美元，复合年增长率为 20.88%。零售边缘运算是指在更靠近资料产生地点（例如零售店或配送中心现场）处理资料的做法，而不是仅依赖远端资料中心或云端平台。该技术利用感测器、摄影机和物联网 (IoT) 系统等边缘设备即时收集、处理和分析资料，使零售商能够更快地做出数据驱动的决策。零售业越来越多地采用边缘运算，因为它可以更快地响应客户需求、更好地管理库存、提供个人化的购物体验并提高营运效率。例如，店内摄影机的即时分析可以优化商店布局，预测消费者行为，甚至透过先进的安全系统减少窃盗。边缘运算透过提供有关库存水准和客户偏好的近乎即时的回馈来增强供应链管理。

市场概况
预测期 2026-2030
2024 年市场规模 48.7 亿美元
2030 年市场规模 151.9 亿美元
2025-2030 年复合年增长率 20.88％
成长最快的领域 中小企业
最大的市场 北美洲

由于几个关键驱动因素，零售边缘运算市场预计将大幅成长。由于客户对即时和客製化服务的期望，对超个人化购物体验的需求日益增长，推动零售商采用能够提供即时洞察的技术。随着零售环境中物联网设备和感测器的数量不断增加，对分散式运算的需求也随之增长，以处理这些设备产生的大量资料。 5G网路的持续扩张进一步加速了这一转变，因为5G实现了高速、低延迟通信，使得边缘运算在处理即时资料方面更加有效。全通路零售的兴起，即消费者透过实体店和数位平台与品牌互动，需要边缘运算能够支援的无缝、反应迅速的系统。由于零售商力求确保高效、安全地处理客户资料，安全问题和减少处理交易时资料延迟的需求也在边缘运算的采用中发挥了一定作用。智慧货架、自动结帐和个人化促销等自动化在零售营运中的重要性日益增加，是推动市场成长的另一个因素。由于边缘运算能够实现更快的本地处理，零售商可以简化营运并增强客户参与度，从而在拥挤的市场中获得更激烈的竞争优势。因此，在技术进步、营运效率需求以及个人化、即时客户体验的推动下，零售边缘运算市场将快速成长。

主要市场驱动因素

即时数据处理和决策的需求

主要市场挑战

与现有基础设施整合的复杂性

主要市场趋势

边缘人工智慧和机器学习的采用率不断提高

目录

第 1 章：解决方案概述

  • 市场定义
  • 市场范围
    • 覆盖市场
    • 考虑学习年限
    • 主要市场区隔

第 2 章：研究方法

第 3 章：执行摘要

第 4 章：顾客之声

第五章：全球零售边缘运算市场概览

第六章：全球零售边缘运算市场展望

  • 市场规模和预测
    • 按价值
  • 市场占有率和预测
    • 按组件（硬体、软体、服务）
    • 按应用（智慧城市、工业物联网、远端监控、内容交付、扩增实境、虚拟实境、其他）
    • 依组织规模（中小型企业、大型企业）
    • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
  • 按公司分类（2024）
  • 市场地图

第七章：北美零售边缘运算市场展望

  • 市场规模和预测
  • 市场占有率和预测
  • 北美：国家分析
    • 加拿大
    • 墨西哥

第 8 章：欧洲零售边缘运算市场展望

  • 市场规模和预测
  • 市场占有率和预测
  • 欧洲：国家分析
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 比利时

第九章：亚太零售边缘运算市场展望

  • 市场规模和预测
  • 市场占有率和预测
  • 亚太地区：国家分析
    • 印度
    • 日本
    • 韩国
    • 澳洲
    • 印尼
    • 越南

第 10 章：南美洲零售边缘运算市场展望

  • 市场规模和预测
  • 市场占有率和预测
  • 南美洲：国家分析
    • 哥伦比亚
    • 阿根廷
    • 智利

第 11 章：中东和非洲零售边缘运算市场展望

  • 市场规模和预测
  • 市场占有率和预测
  • 中东和非洲：国家分析
    • 阿联酋
    • 南非
    • 土耳其
    • 以色列

第 12 章：市场动态

  • 驱动程式
  • 挑战

第 13 章：市场趋势与发展

第 14 章：公司简介

  • Amazon.com, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Intel Corporation
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise Company
  • NVIDIA Corporation
  • Google LLC
  • Oracle Corporation
  • Qualcomm Incorporated

第 15 章：策略建议

第16章调查会社について・免责事项

简介目录
Product Code: 27516

The Global Retail Edge Computing Market was valued at USD 4.87 billion in 2024 and is expected to reach USD 15.19 billion by 2030 with a CAGR of 20.88% through 2030. Retail Edge Computing refers to the practice of processing data closer to the location where it is generated, such as on-site at retail stores or distribution centers, rather than relying solely on distant data centers or cloud platforms. This technology leverages edge devices like sensors, cameras, and IoT (Internet of Things) systems to collect, process, and analyze data in real time, enabling retailers to make faster, data-driven decisions. The retail sector has been increasingly adopting edge computing as it allows for quicker responses to customer needs, better inventory management, personalized shopping experiences, and improved operational efficiency. For example, real-time analytics from in-store cameras can optimize store layouts, predict consumer behavior, and even reduce theft through advanced security systems. Edge computing enhances supply chain management by providing near-instantaneous feedback on inventory levels and customer preferences.

Market Overview
Forecast Period2026-2030
Market Size 2024USD 4.87 Billion
Market Size 2030USD 15.19 Billion
CAGR 2025-203020.88%
Fastest Growing SegmentSmall & Medium Enterprises
Largest MarketNorth America

The market for retail edge computing is expected to rise significantly due to several key drivers. The growing demand for hyper-personalized shopping experiences, driven by customer expectations for instant and tailored services, is pushing retailers to adopt technologies that can provide real-time insights. As the number of IoT devices and sensors in retail environments continues to increase, the need for decentralized computing grows to handle the massive volume of data these devices generate. The ongoing expansion of 5G networks further accelerates this shift, as 5G enables high-speed, low-latency communication, making edge computing more effective in handling real-time data processing. The rise of omnichannel retail, where consumers interact with brands through both physical stores and digital platforms, demands seamless and responsive systems that edge computing can support. Security concerns and the need for reducing data latency in processing transactions also play a role in the adoption of edge computing, as retailers seek to ensure customer data is handled efficiently and securely. The increasing importance of automation in retail operations, such as smart shelves, automated checkout, and personalized promotions, is another factor driving the market's growth. As edge computing enables faster, local processing, retailers can streamline operations and enhance customer engagement, leading to more competitive advantages in a crowded market. Therefore, the retail edge computing market is poised to grow rapidly, driven by advancements in technology, the need for operational efficiency, and the push for personalized, real-time customer experiences.

Key Market Drivers

Demand for Real-Time Data Processing and Decision Making

One of the primary drivers of the retail edge computing market is the increasing demand for real-time data processing and decision making within retail environments. The modern retail landscape is becoming increasingly data-driven, with retailers collecting vast amounts of information from in-store sensors, cameras, point-of-sale systems, and online interactions. These data points include customer behavior, inventory levels, and transaction details. For retail businesses, the ability to process this information as it is generated, without having to send it to a centralized cloud or data center, has become a critical factor in staying competitive. Retailers are under constant pressure to improve customer experiences, optimize operations, and stay ahead of market trends. Real-time data processing allows them to gain immediate insights into their operations, whether it is for analyzing customer foot traffic, adjusting pricing, or making stock replenishment decisions. Edge computing enables data to be processed closer to the point of origin, reducing latency and enabling quicker decision-making, which is especially crucial during peak hours or sales events. For instance, by leveraging real-time data at the edge, a retailer can adjust promotions, manage store layouts, and even optimize staff allocation instantly based on customer behavior patterns, thereby enhancing operational efficiency and improving customer experience. This ability to make informed decisions promptly is a major factor driving the retail edge computing market's growth. By the end of 2025, it is estimated that 80% of all enterprise data will need to be processed in real-time or near real-time to drive critical decision-making.

Key Market Challenges

Complexity of Integration with Existing Infrastructure

One of the primary challenges for the retail edge computing market is the complexity of integrating edge computing solutions with existing retail infrastructure. Many retailers, particularly legacy businesses, already have established systems in place for their operations, such as centralized data centers, cloud-based applications, and traditional point-of-sale systems. Implementing edge computing requires significant changes to this infrastructure, which can be costly, time-consuming, and technically challenging. Retailers must ensure that their edge computing solutions are seamlessly integrated with these legacy systems to maintain smooth operations and avoid disruptions. This can involve substantial investments in both hardware and software, as well as training personnel to manage and operate new systems. Many edge computing solutions require specialized hardware, such as local data processing units, sensors, or specialized network equipment, which may not be compatible with older retail technologies. Integrating such diverse systems can lead to compatibility issues, data silos, or inefficiencies that hinder the desired performance improvements. The process of integration may involve significant customization to align with the specific needs of a retail business. Retailers must work closely with technology vendors and service providers to ensure that edge computing solutions are tailored to their particular operational requirements, which can increase project timelines and costs. For businesses with a wide range of store formats or a diverse product offering, integrating edge computing at scale can be particularly challenging. A lack of standardized solutions or processes across different retail environments can create inconsistencies in performance and operational challenges, delaying the expected benefits of edge computing. Thus, retailers face considerable challenges in ensuring that edge computing solutions can be effectively incorporated into their existing infrastructure while maintaining operational continuity.

Key Market Trends

Increased Adoption of Artificial Intelligence and Machine Learning at the Edge

One of the significant trends in the retail edge computing market is the increasing integration of artificial intelligence and machine learning technologies directly at the edge. Traditionally, artificial intelligence and machine learning models required heavy processing power in centralized cloud environments, resulting in latency and bandwidth challenges. However, with the advancement of edge computing technologies, retailers are now able to deploy these advanced algorithms at the edge, closer to where data is generated. This enables real-time analysis of customer behavior, inventory management, and store operations. For example, edge devices equipped with artificial intelligence can instantly analyze video feeds from in-store cameras to recognize customer actions, detect patterns, and even predict future purchasing behavior. Retailers can leverage this data to offer personalized promotions, optimize store layouts, or detect shoplifting in real-time. Machine learning algorithms can be used to predict inventory needs based on in-store data, reducing stockouts and overstocking. The ability to run these sophisticated models locally ensures quicker response times and minimizes the need for constant cloud communication, which enhances overall system efficiency. The growing reliance on artificial intelligence and machine learning at the edge is transforming how retailers operate, providing them with enhanced insights and decision-making capabilities that drive business success.

Key Market Players

  • Amazon.com, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Intel Corporation
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise Company
  • NVIDIA Corporation
  • Google LLC
  • Oracle Corporation
  • Qualcomm Incorporated

Report Scope:

In this report, the Global Retail Edge Computing Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Retail Edge Computing Market, By Component:

  • Hardware
  • Software
  • Services

Retail Edge Computing Market, By Application:

  • Smart Cities
  • Industrial Internet of Things
  • Remote Monitoring
  • Content Delivery
  • Augmented Reality
  • Virtual Reality
  • Others

Retail Edge Computing Market, By Organization Size:

  • Small & Medium Enterprises
  • Large Enterprises

Retail Edge Computing Market, By Region:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Belgium
  • Asia Pacific
    • China
    • India
    • Japan
    • South Korea
    • Australia
    • Indonesia
    • Vietnam
  • South America
    • Brazil
    • Colombia
    • Argentina
    • Chile
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Turkey
    • Israel

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Retail Edge Computing Market.

Available Customizations:

Global Retail Edge Computing Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Solution Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Formulation of the Scope
  • 2.4. Assumptions and Limitations
  • 2.5. Sources of Research
    • 2.5.1. Secondary Research
    • 2.5.2. Primary Research
  • 2.6. Approach for the Market Study
    • 2.6.1. The Bottom-Up Approach
    • 2.6.2. The Top-Down Approach
  • 2.7. Methodology Followed for Calculation of Market Size & Market Shares
  • 2.8. Forecasting Methodology
    • 2.8.1. Data Triangulation & Validation

3. Executive Summary

4. Voice of Customer

5. Global Retail Edge Computing Market Overview

6. Global Retail Edge Computing Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component (Hardware, Software, Services)
    • 6.2.2. By Application (Smart Cities, Industrial Internet of Things, Remote Monitoring, Content Delivery, Augmented Reality, Virtual Reality, Others)
    • 6.2.3. By Organization Size (Small & Medium Enterprises, Large Enterprises)
    • 6.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 6.3. By Company (2024)
  • 6.4. Market Map

7. North America Retail Edge Computing Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component
    • 7.2.2. By Application
    • 7.2.3. By Organization Size
    • 7.2.4. By Country
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Retail Edge Computing Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Component
        • 7.3.1.2.2. By Application
        • 7.3.1.2.3. By Organization Size
    • 7.3.2. Canada Retail Edge Computing Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Component
        • 7.3.2.2.2. By Application
        • 7.3.2.2.3. By Organization Size
    • 7.3.3. Mexico Retail Edge Computing Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Component
        • 7.3.3.2.2. By Application
        • 7.3.3.2.3. By Organization Size

8. Europe Retail Edge Computing Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Application
    • 8.2.3. By Organization Size
    • 8.2.4. By Country
  • 8.3. Europe: Country Analysis
    • 8.3.1. Germany Retail Edge Computing Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Application
        • 8.3.1.2.3. By Organization Size
    • 8.3.2. France Retail Edge Computing Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Application
        • 8.3.2.2.3. By Organization Size
    • 8.3.3. United Kingdom Retail Edge Computing Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Application
        • 8.3.3.2.3. By Organization Size
    • 8.3.4. Italy Retail Edge Computing Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Component
        • 8.3.4.2.2. By Application
        • 8.3.4.2.3. By Organization Size
    • 8.3.5. Spain Retail Edge Computing Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Component
        • 8.3.5.2.2. By Application
        • 8.3.5.2.3. By Organization Size
    • 8.3.6. Belgium Retail Edge Computing Market Outlook
      • 8.3.6.1. Market Size & Forecast
        • 8.3.6.1.1. By Value
      • 8.3.6.2. Market Share & Forecast
        • 8.3.6.2.1. By Component
        • 8.3.6.2.2. By Application
        • 8.3.6.2.3. By Organization Size

9. Asia Pacific Retail Edge Computing Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Application
    • 9.2.3. By Organization Size
    • 9.2.4. By Country
  • 9.3. Asia Pacific: Country Analysis
    • 9.3.1. China Retail Edge Computing Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Application
        • 9.3.1.2.3. By Organization Size
    • 9.3.2. India Retail Edge Computing Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Application
        • 9.3.2.2.3. By Organization Size
    • 9.3.3. Japan Retail Edge Computing Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Application
        • 9.3.3.2.3. By Organization Size
    • 9.3.4. South Korea Retail Edge Computing Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Component
        • 9.3.4.2.2. By Application
        • 9.3.4.2.3. By Organization Size
    • 9.3.5. Australia Retail Edge Computing Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Component
        • 9.3.5.2.2. By Application
        • 9.3.5.2.3. By Organization Size
    • 9.3.6. Indonesia Retail Edge Computing Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Component
        • 9.3.6.2.2. By Application
        • 9.3.6.2.3. By Organization Size
    • 9.3.7. Vietnam Retail Edge Computing Market Outlook
      • 9.3.7.1. Market Size & Forecast
        • 9.3.7.1.1. By Value
      • 9.3.7.2. Market Share & Forecast
        • 9.3.7.2.1. By Component
        • 9.3.7.2.2. By Application
        • 9.3.7.2.3. By Organization Size

10. South America Retail Edge Computing Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Application
    • 10.2.3. By Organization Size
    • 10.2.4. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Retail Edge Computing Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Application
        • 10.3.1.2.3. By Organization Size
    • 10.3.2. Colombia Retail Edge Computing Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Application
        • 10.3.2.2.3. By Organization Size
    • 10.3.3. Argentina Retail Edge Computing Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Application
        • 10.3.3.2.3. By Organization Size
    • 10.3.4. Chile Retail Edge Computing Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Component
        • 10.3.4.2.2. By Application
        • 10.3.4.2.3. By Organization Size

11. Middle East & Africa Retail Edge Computing Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Component
    • 11.2.2. By Application
    • 11.2.3. By Organization Size
    • 11.2.4. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Retail Edge Computing Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Component
        • 11.3.1.2.2. By Application
        • 11.3.1.2.3. By Organization Size
    • 11.3.2. UAE Retail Edge Computing Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Component
        • 11.3.2.2.2. By Application
        • 11.3.2.2.3. By Organization Size
    • 11.3.3. South Africa Retail Edge Computing Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Component
        • 11.3.3.2.2. By Application
        • 11.3.3.2.3. By Organization Size
    • 11.3.4. Turkey Retail Edge Computing Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Component
        • 11.3.4.2.2. By Application
        • 11.3.4.2.3. By Organization Size
    • 11.3.5. Israel Retail Edge Computing Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Component
        • 11.3.5.2.2. By Application
        • 11.3.5.2.3. By Organization Size

12. Market Dynamics

  • 12.1. Drivers
  • 12.2. Challenges

13. Market Trends and Developments

14. Company Profiles

  • 14.1. Amazon.com, Inc.
    • 14.1.1. Business Overview
    • 14.1.2. Key Revenue and Financials
    • 14.1.3. Recent Developments
    • 14.1.4. Key Personnel/Key Contact Person
    • 14.1.5. Key Product/Services Offered
  • 14.2. Microsoft Corporation
    • 14.2.1. Business Overview
    • 14.2.2. Key Revenue and Financials
    • 14.2.3. Recent Developments
    • 14.2.4. Key Personnel/Key Contact Person
    • 14.2.5. Key Product/Services Offered
  • 14.3. IBM Corporation
    • 14.3.1. Business Overview
    • 14.3.2. Key Revenue and Financials
    • 14.3.3. Recent Developments
    • 14.3.4. Key Personnel/Key Contact Person
    • 14.3.5. Key Product/Services Offered
  • 14.4. Intel Corporation
    • 14.4.1. Business Overview
    • 14.4.2. Key Revenue and Financials
    • 14.4.3. Recent Developments
    • 14.4.4. Key Personnel/Key Contact Person
    • 14.4.5. Key Product/Services Offered
  • 14.5. Cisco Systems, Inc.
    • 14.5.1. Business Overview
    • 14.5.2. Key Revenue and Financials
    • 14.5.3. Recent Developments
    • 14.5.4. Key Personnel/Key Contact Person
    • 14.5.5. Key Product/Services Offered
  • 14.6. Hewlett Packard Enterprise Company
    • 14.6.1. Business Overview
    • 14.6.2. Key Revenue and Financials
    • 14.6.3. Recent Developments
    • 14.6.4. Key Personnel/Key Contact Person
    • 14.6.5. Key Product/Services Offered
  • 14.7. NVIDIA Corporation
    • 14.7.1. Business Overview
    • 14.7.2. Key Revenue and Financials
    • 14.7.3. Recent Developments
    • 14.7.4. Key Personnel/Key Contact Person
    • 14.7.5. Key Product/Services Offered
  • 14.8. Google LLC
    • 14.8.1. Business Overview
    • 14.8.2. Key Revenue and Financials
    • 14.8.3. Recent Developments
    • 14.8.4. Key Personnel/Key Contact Person
    • 14.8.5. Key Product/Services Offered
  • 14.9. Oracle Corporation
    • 14.9.1. Business Overview
    • 14.9.2. Key Revenue and Financials
    • 14.9.3. Recent Developments
    • 14.9.4. Key Personnel/Key Contact Person
    • 14.9.5. Key Product/Services Offered
  • 14.10. Qualcomm Incorporated
    • 14.10.1. Business Overview
    • 14.10.2. Key Revenue and Financials
    • 14.10.3. Recent Developments
    • 14.10.4. Key Personnel/Key Contact Person
    • 14.10.5. Key Product/Services Offered

15. Strategic Recommendations

16. About Us & Disclaimer