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市場調查報告書

邊緣分析的全球市場:成長,趨勢,及預測(2019年∼2024年)

Edge Analytics Market - Growth, Trends and Forecast (2020 - 2025)

出版商 Mordor Intelligence LLP 商品編碼 670001
出版日期 內容資訊 英文 127 Pages
商品交期: 2-3個工作天內
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邊緣分析的全球市場:成長,趨勢,及預測(2019年∼2024年) Edge Analytics Market - Growth, Trends and Forecast (2020 - 2025)
出版日期: 2020年01月01日內容資訊: 英文 127 Pages
簡介

本報告提供全球邊緣分析市場的相關調查,市場機會和趨勢,成長要素及課題,各展開類型、零組件、終端用戶產業、地區的市場分析,競爭情形,主要企業的簡介等資訊。

目錄

第1章 簡介

  • 調查的前提條件
  • 調查範圍

第2章 調查方法

第3章 摘要整理

第4章 市場動態

  • 市場概況
  • 成長要素
  • 市場課題
  • 產業價值鏈分析
  • 產業的魅力:波特的五力分析
    • 新加入廠商的威脅
    • 買主/消費者談判力
    • 供應商談判力
    • 替代產品的威脅
    • 產業內的競爭
  • 技術概述
    • 說明分析
    • 預測分析
    • 規範的分析
    • 診斷分析

第5章 市場區隔

  • 各部署類型
    • 內部部署
    • 雲端
  • 各零件
    • 解決方案
    • 服務(專業、管理服務)
  • 各終端用戶產業
    • 銀行、金融服務、及保險(BFSI)
    • IT、通訊
    • 製造業
    • 醫療保健
    • 零售
    • 其他
  • 各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 其他

第6章 競爭情形

  • 企業簡介
    • Cisco Systems Inc.
    • Oracle Corporation
    • SAS Institute Inc.
    • IBM Corporation
    • Apigee Corporation
    • Predixion Software
    • AGT International Inc.
    • Foghorn Systems
    • CGI Group Inc.
    • Intel Corporation
    • Greenwave Systems
    • Microsoft Corporation

第7章 市場機會及今後趨勢

第8章 投資分析

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目錄
Product Code: 62346

Market Overview

The Edge Analytics Market was valued at USD 3.54 billion in 2019 and is expected to reach USD 17.13 billion by 2025, at a CAGR of 30% over the forecast period 2020 - 2025. Edge analytics, an alternative to big data analytics, provides real-time analysis of data generated on the edge of network devices, which is in an unstructured form. Edge analytics performs the automatic analytical computation of collected data in real-time, instead of sending the data back to the centralized data store or server. Edge Analytics is increasing at significant force across the world, owing to the constant advancements of workplace performance enhancements and increase adoption of internet of things (IoT), which are driving the edge analytics market growth to the large extent. Moreover, its distinctive features like cost optimization and scalability are significantly boosting the growth of the market.

  • Edge analytics help companies to get more advanced data faster by employing advanced analytics and machine learning at the point of data collection. Also, it further boosts yields, increases throughput, reduces downtime, and improves efficiency. It is gaining increasing demand owing to the emergence and the booming expansion of the Internet of Things (IoT) and the fast-paced growth in the availability of data through connected devices and via real-time intelligence.
  • The manufacturing industry can make extensive use of Edge analytics, for instance, in a smart production line. Pointing out manufacturing defects or anomalies, badly printed stickers, packaging, etc., in real-time can be achieved using edge analytics. Further, by embedding computing capability in the form of complex event processing (CPE), edge devices can filter out noisy data and collect only information that is deemed useful.
  • Healthcare is another domain where a massive surge in the number of connected devices can be witnessed. In the future, a hospital room on an average will have around 15 to 20 medical devices, a majority of which are expected to be networked. A large hospital can have as much as 85,000 connected medical and IoT devices, putting a significant strain on the cloud network. Edge analytics and computing can reduce this burden to a great extent.

Scope of the Report

Edge analytics is a way to data collection and interpretation in which a programmed analytical computation is performed on data at a sensor, network switch or another device instead of waiting for the data to be sent back to a centralized data store.

Key Market Trends

Retail Industry to Drive the Edge Analytics Market

  • With a traditional data warehouse model, it takes significant bandwidth, time, and cost to transmit all the data to a central repository and extract the insights required to improve operations or customer interactions. Using edge analytics, retailers will be able to analyze all types of data real-time and capture fleeting opportunities to deliver hyper-relevant customer experiences and optimize operations, such as streamlining the checkout or ensuring items are in stock.
  • Retail is experiencing huge data that is generating from the video camera installed in the store, in-store Wi-Fi networks, sensors, and data generated from apps. Much of the produced data is unstructured in nature, which provides valuable information. Leading retailers are utilizing edge analytics to deliver better user experience and maximize store performance. From location analytics to drive engagement to understand shopper's pattern, retail giants Target and Walmart, among others, are using analytics at the edge of the network to draw insights from terabytes of data.
  • Retailers can leverage data from a range of sensors including parking lot sensors, shopping cart tags, and store cameras. By applying smart analytics to the data, they can predict checkout wait times and preemptively alert store service managers when more registers are required to be opened, or even automatically open registers before customers get there. It also helps retailers to change their business model and reform their strategies to main competitive edge. The idea is not limited to targeting a group of audiences but offering personalized solutions for everyone with the help of behavioral targeting.

North America Holds the Largest Share in Edge Analytics Market

The United States remains a prominent market for Edge Analytics, due to increasing acceptance of edge analytics among small and medium-scale firms, supported by government regulations and compliance. Additionally, significant growth of the edge analytics market can be attributed to the high concentration of manufacturing and telecommunication industries that majorly adopt edge analytics services. The demand for edge analytics is directly related to cloud traffic. Due to the huge increase in cloud traffic, significant growth in the market can be observed.

North American Insurance companies are changing the way they utilize cloud computing. While both property & casualty and life insurers have employed cloud to increase agility, increase operating efficiency, attract new talent and reduce operating costs, there is an emerging trend in insurers viewing the cloud as a business asset. Cloud operations cost can be significantly reduced by using a distributed edge computing architecture, where edge devices together process a critical operation, which a cloud device cannot process on its own, thereby reducing cloud dependency.

Also, significant growth in sensor technology can be witnessed in the region. By combining the innovations of sensor technology with reducing hardware costs, the edge-to-cloud paradigm can be established. Sensors with processing units can help take critical actions in an inconsistent cloud environment and can later synchronize with the cloud.

Competitive Landscape

The edge analytics market is extremely competing and consists of numerous significant players. In terms of market share, few of the significant players currently control the market. These important players with a noticeable share in the market are concentrating on growing their customer base across foreign countries. These businesses are leveraging strategic collaborative initiatives to enhance their market share and improve their profitability.

May 2018 - Wood and IBM collaborated to transform the asset life cycle management. This partnership will help create and offer new digital products and services that can help increase operational efficiencies for customers in the industrial and energy markets. The transformation was realized with the help of the edge analytics suite of IBM.

Mar 2019 - FogHorn, announced NTT Data, a trusted global innovator delivering technology-enabled services and solutions to clients around the world, has selected its Lightning software to deliver on-premise real-time analytics and AI to their industrial clients. NTT Data offers deep expertise and IoT consulting and integration services which are utilized by FogHorn in the manufacturing, telecommunications, and energy industries.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • Report customization as per the client's requirements
  • 3 months of analyst support

Table of Contents

1 INTRODUCTION

  • 1.1 Study Assumptions
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Growth in Number of Connected Devices in IoT
    • 4.2.2 Rising Propagation of Data Over Connected Devices
  • 4.3 Market Challenges
    • 4.3.1 Edge technology Adoption is Still in Early Stage
    • 4.3.2 Threat of Data Safety and Security
  • 4.4 Industry Value Chain Analysis
  • 4.5 Industry Attractiveness - Porter's Five Force Analysis
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry
  • 4.6 Technology Snapshot
    • 4.6.1 Descriptive Analytics
    • 4.6.2 Predictive Analytics
    • 4.6.3 Prescriptive Analytics
    • 4.6.4 Diagnostic Analytics

5 MARKET SEGMENTATION

  • 5.1 By Deployment Type
    • 5.1.1 On-Premises
    • 5.1.2 Cloud
  • 5.2 By Component
    • 5.2.1 Solutions
    • 5.2.2 Services (Professional and Managed Services)
  • 5.3 By End User Industry
    • 5.3.1 Banking, Financial Services, and Insurance (BFSI)
    • 5.3.2 IT & Telecommunication
    • 5.3.3 Manufacturing
    • 5.3.4 Healthcare
    • 5.3.5 Retail
    • 5.3.6 Other End-user Industry
  • 5.4 Geography
    • 5.4.1 North America
      • 5.4.1.1 United States
      • 5.4.1.2 Canada
    • 5.4.2 Europe
      • 5.4.2.1 United Kingdom
      • 5.4.2.2 Germany
      • 5.4.2.3 France
      • 5.4.2.4 Rest of Europe
    • 5.4.3 Asia-Pacific
      • 5.4.3.1 Japan
      • 5.4.3.2 China
      • 5.4.3.3 India
      • 5.4.3.4 Rest of Asia-Pacific
    • 5.4.4 Rest of the World

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 Cisco Systems Inc.
    • 6.1.2 Oracle Corporation
    • 6.1.3 SAS Institute Inc.
    • 6.1.4 IBM Corporation
    • 6.1.5 Apigee Corporation
    • 6.1.6 Predixion Software
    • 6.1.7 AGT International Inc.
    • 6.1.8 Foghorn Systems
    • 6.1.9 CGI Group Inc.
    • 6.1.10 Intel Corporation
    • 6.1.11 Greenwave Systems
    • 6.1.12 Microsoft Corporation

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

8 INVESTMENT ANALYSIS

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