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MLaaS(Machine Learning as a Service的)全球市場 - 產業規模，佔有率，趨勢，機會，預測:各零件，各組織規模，各用途，各終端用戶，各地區，各競爭(2018年～2028年)
市場調查報告書
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1166604

MLaaS(Machine Learning as a Service的)全球市場 - 產業規模，佔有率，趨勢，機會，預測:各零件，各組織規模，各用途，各終端用戶，各地區，各競爭(2018年～2028年)

Machine Learning as a Service Market- Global Industry Size, Share, Trends, Opportunities, and Forecast 2018-2028F Segmented By Component, By Organization Size, By Application, By End User, By Region, Competition
出版日期: | 出版商: TechSci Research | 英文 74 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球MLaaS(Machine Learning as a Service的)市場規模，預計至2028年以2位數的年複合成長率成長。

市場成長的要素，是雲端基礎的解決方案的日益採用，巨量資料的用途持續增加。再加上技術純熟勞工少，及資料保全的缺乏，在整個預測期內估計有阻礙全球MLaaS(Machine Learning as a Service)市場成長的可能性。

本報告提供全球MLaaS(Machine Learning as a Service)市場相關調查，市場概要，VOC分析，各市場區隔、各地區的預測，促進因素和課題，COVID-19影響，市場趨勢，企業簡介等資訊。

目錄

第1章 服務概要

第2章 調查手法

第3章 摘要整理

第4章 全球MLaaS(Machine Learning as a Service)市場上COVID-19的影響

第5章 VOC

  • MLaaS(Machine Learning as a Service的)認知度
  • MLaaS(Machine Learning as a Service的)主要用途
  • MLaaS(Machine Learning as a Service)的主要的優點
  • 主要供應商選擇的參數
  • MLaaS(Machine Learning as a Service)採用時主要的選擇範圍
  • 主要供應商的課題

第6章 全球MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件(解決方案，服務)
    • 各組織規模(大企業，中小企業)
    • 各用途(銀行、金融服務、保險，醫療保健、醫藥品，電子商務、零售，媒體、娛樂，IT、通訊，其他)
    • 各終端用戶(IT、通訊，汽車，醫療保健，航太、防衛，零售，政府，銀行、金融服務、保險)
    • 各地區
    • 重要點
    • 各企業
  • 市場地圖(各零件，各組織規模，各用途，各終端用戶，各地區)

第7章 北美的MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件
    • 各組織規模
    • 各用途
    • 各終端用戶
    • 各國
    • 重要點
  • 北美:各國分析
    • 美國
    • 加拿大
    • 墨西哥

第8章 歐洲的MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件
    • 各組織規模
    • 各用途
    • 各終端用戶
    • 各國
    • 重要點
  • 歐洲:各國分析
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙

第9章 亞太地區的MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件
    • 各組織規模
    • 各用途
    • 各終端用戶
    • 各國
    • 重要點
  • 亞太地區:各國分析
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲

第10章 中東、非洲的MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件
    • 各組織規模
    • 各用途
    • 各終端用戶
    • 各國
    • 重要點
  • 中東、非洲:各國分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第11章 南美的MLaaS(Machine Learning as a Service)市場預測

  • 市場規模與預測
    • 各金額
  • 市場佔有率與預測
    • 各零件
    • 各組織規模
    • 各用途
    • 各終端用戶
    • 各國
    • 重要點
  • 南美:各國分析
    • 巴西
    • 阿根廷
    • 哥倫比亞

第12章 市場動態

  • 促進因素
  • 課題

第13章 市場趨勢與發展

  • 客戶支援活動增加
  • 智慧後勤部門和營運
  • 在零售領域的機器學習的使用增加
  • 合併和收購
  • 巨量資料的急劇成長

第14章 企業簡介

  • Google Inc
  • SAS Institute Inc
  • Fair Isaac Corporation
  • Hewlett Packard Enterprise Development LP
  • Yottamine Analytics Inc.
  • Amazon Web Services
  • BigML, Inc.
  • Microsoft Corporation
  • IBM Corporation
  • Broadcom Corporation

第15章 策略性建議

第16章 免責聲明

簡介目錄
Product Code: 14234

Global machine learning as a service market is anticipated to grow at double digit CAGR through 2028 on account of rising adoption of cloud-based solutions and increasing application of big data. Additionally, it is estimated that the limited availability of skilled labour and a lack of data security can hamper the growth of the machine learning as a service (MLaaS) market globally throughout the forecasted period. The term "Machine Learning as a Service" (MLaaS) refers to a group of services which includes several cloud-based platforms using machine learning techniques to offer dedicated solutions. Furthermore, MLaaS reduces infrastructure-related issues such as data pre-processing, model training, model evaluation, and, ultimately, predictions.

Rising adoption of cloud-based services

, Several industry verticals utilize major cloud-based solutions to manage business operations. With cloud-based technologies being majorly used in various organizations and enterprises; data interchange is facilitated by the simplicity with which these connections are established. This makes it possible to access the information within the organization, increasing the latter's cost-effectiveness. For instance, Infosys Ltd launched industry cloud platform for organizations in 2022 to increase innovation and business value in the cloud across the financial services industry.

Lack of skilled resources

Developers can now design efficient cloud-based business operation solutions with the expanding adoption of cloud technologies and desirable delivery techniques across numerous industry verticals. To speed up the ML integration process, SMEs in the MLaaS industry prefer cloud-based services. Eliminating tedious work improves an organization's efficiency without adding more people. Though, lack of trained consultants, compliance problems, and regulatory limitations are some obstacles preventing this market's expansion. Therefore, in order to improve uniformity in the market environment, market participants should collaborate with governmental and regulatory agencies to improve the uniformity in the market environment.

Growing IoT in business operations

The information technology industry is expanding due to the increasing popularity of social media platforms and cloud computing technologies. Today, cloud computing services are extensively used by various companies that offer enterprise storage solutions. The ability to analyze real time data online using cloud storage is a benefit. Thanks to cloud computing, data analysis is now possible at any time and location. Businesses may also digitally access critical data from linked data warehouses and save money on infrastructure and storage costs by utilizing cloud and ML, which includes trends in customer behaviour and purchasing. The growth of cloud computing has led to the development of MLaaS industry. AI systems employ ML to speed up learning, self-correction, and reasoning. AI applications include expert systems, speech recognition, and machine vision, to name a few. Hence, AI is becoming increasingly popular as a result of modern initiatives like big data infrastructure and cloud computing.

Market Segments

Global Machine Learning as a Service Market is segmented into by component, by organization size, by application, by end-user and by region. Based on component, the market is segmented into Solution and Service. Based on Organization Size, the market is segmented into Small and Medium-Sized Enterprises and Large Enterprises. Based on Application, the market is segmented into Marketing & Advertising, Fraud Detection & Risk Management, Computer vision, Security & Surveillance, Predictive analytics, Natural Language Processing, Augmented & Virtual Reality, Others. Based on End User, the market is further segmented into IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI.

Market Players

Major market players in the Global Machine Learning as a Service Market are Google Inc, SAS Institute Inc, Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, Yottamine Analytics Inc., Amazon Web Services, BigML, Inc., Microsoft Corporation, IBM Corporation, Broadcom Corporation

Recent Developments

  • Inflection AI received one of the largest fundraising rounds for artificial machine learning in June 2022, amounting to USD 225 million. It is said to be a startup for AI and machine learning. Venture capitalists have provided it with equity financing worth USD 225 million.
  • Vertex AI, a new managed machine learning platform that enables users to maintain and deploy AI models based on client needs, was announced by Google Cloud in May 2021.

Report Scope:

In this report, Global Machine Learning as a Service Market has been segmented into following categories, in addition to the industry trends which have also been detailed below:

  • Machine Learning as a Service Market, By Component:

Solution

Service

  • Machine Learning as a Service Market, By Organization Size:

Small and Medium-Sized Enterprises

Large Enterprises

  • Machine Learning as a Service Market, By Application:

Marketing & Advertising

Fraud Detection & Risk Management

Computer vision

Security & Surveillance

Predictive analytics

Natural Language Processing

Augmented & Virtual Reality

Others

  • Machine Learning as a Service Market, By End User:

IT and Telecom

Automotive

Healthcare

Aerospace and Defense

Retail

Government

BFSI

  • Machine Learning as a Service Market, By Region:

North America

  • United States
  • Canada
  • Mexico

Asia-Pacific

  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Rest of Asia-Pacific

Europe

  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe

MEA

  • Saudi Arabia
  • UAE
  • South Africa
  • Rest of MEA

South America

  • Brazil
  • Argentina
  • Colombia
  • Rest of South America

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in Global Machine Learning as a Service Market.

Available Customizations:

Global Machine Learning as a Service Market with the given market data, Tech Sci 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. Service Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Study

2. Research Methodology

  • 2.1. Baseline Methodology
  • 2.2. Methodology Followed for Calculation of Market Size
  • 2.3. Methodology Followed for Calculation of Market Shares
  • 2.4. Methodology Followed for Forecasting

3. Executive Summary

4. Impact of COVID-19 on Global Machine Learning as a Service Market

5. Voice of Customer

  • 5.1. Awareness of Machine Learning as a Service
  • 5.2. Major Applications of Machine Learning as a Service
  • 5.3. Key benefits of Machine Learning as a Service
  • 5.4. Key vendor selection parameter
  • 5.5. Major selection in adopting Machine Learning as a Service
  • 5.6. Key vendor challenges

6. Global Machine Learning as a Service Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component (Solution, Service)
    • 6.2.2. By Organization Size (Large Enterprises, Small and Medium-Sized Enterprises)
    • 6.2.3. By Application (BFSI, Healthcare & Pharmaceuticals, E-commerce & Retail, Media & Entertainment, IT & Telecom, and Others)
    • 6.2.4. By End-User (IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI)
    • 6.2.5. By Region
    • 6.2.6. Key Takeaways
    • 6.2.7. By Company (2022)
  • 6.3. Market Map (By Component, By Organization Size, By Application, By End-User, By Region)

7. North America Machine Learning as a Service 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 Organization Size
    • 7.2.3. By Application
    • 7.2.4. By End-User
    • 7.2.5. By Country
    • 7.2.6. Key Takeaways
  • 7.3. North America: Country Analysis
    • 7.3.1. United States Machine Learning as a Service 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 Organization Size
        • 7.3.1.2.3. By Application
        • 7.3.1.2.4. By End-User
    • 7.3.2. Canada Machine Learning as a Service 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 Organization Size
        • 7.3.2.2.3. By Application
        • 7.3.2.2.4. By End-User
    • 7.3.3. Mexico Machine Learning as a Service 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 Organization Size
        • 7.3.3.2.3. By Application
        • 7.3.3.2.4. By End-User

8. Europe Machine Learning as a Service 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 Organization Size
    • 8.2.3. By Application
    • 8.2.4. By End-User
    • 8.2.5. By Country
    • 8.2.6. Key Takeaways
  • 8.3. Europe: Country Analysis
    • 8.3.1. Germany Machine Learning as a Service 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 Organization Size
        • 8.3.1.2.3. By Application
        • 8.3.1.2.4. By End-User
    • 8.3.2. United Kingdom Machine Learning as a Service 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 Organization Size
        • 8.3.2.2.3. By Application
        • 8.3.2.2.4. By End-User
    • 8.3.3. France Machine Learning as a Service 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 Organization Size
        • 8.3.3.2.3. By Application
        • 8.3.3.2.4. By End-User
    • 8.3.4. Italy Machine Learning as a Service 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 Organization Size
        • 8.3.4.2.3. By Application
        • 8.3.4.2.4. By End-User
    • 8.3.5. Spain Machine Learning as a Service 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 Organization Size
        • 8.3.5.2.3. By Application
        • 8.3.5.2.4. By End-User

9. Asia Pacific Machine Learning as a Service 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 Organization Size
    • 9.2.3. By Application
    • 9.2.4. By End-User
    • 9.2.5. By Country
    • 9.2.6. Key Takeaways
  • 9.3. Asia Pacific: Country Analysis
    • 9.3.1. China Machine Learning as a Service 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 Organization Size
        • 9.3.1.2.3. By Application
        • 9.3.1.2.4. By End-User
    • 9.3.2. Japan Machine Learning as a Service 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 Organization Size
        • 9.3.2.2.3. By Application
        • 9.3.2.2.4. By End-User
    • 9.3.3. India Machine Learning as a Service 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 Organization Size
        • 9.3.3.2.3. By Application
        • 9.3.3.2.4. By End-User
    • 9.3.4. South Korea Machine Learning as a Service 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 Organization Size
        • 9.3.4.2.3. By Application
        • 9.3.4.2.4. By End-User
    • 9.3.5. Australia Machine Learning as a Service 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 Organization Size
        • 9.3.5.2.3. By Application
        • 9.3.5.2.4. By End-User

10. Middle East & Africa Machine Learning as a Service 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 Organization Size
    • 10.2.3. By Application
    • 10.2.4. By End-User
    • 10.2.5. By Country
    • 10.2.6. Key Takeaways
  • 10.3. Middle East & Africa: Country Analysis
    • 10.3.1. Saudi Arabia Machine Learning as a Service 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 Organization Size
        • 10.3.1.2.3. By Application
        • 10.3.1.2.4. By End-User
    • 10.3.2. UAE Machine Learning as a Service 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 Organization Size
        • 10.3.2.2.3. By Application
        • 10.3.2.2.4. By End-User
    • 10.3.3. South Africa Machine Learning as a Service 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 Organization Size
        • 10.3.3.2.3. By Application
        • 10.3.3.2.4. By End-User

11. South America Machine Learning as a Service 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 Organization Size
    • 11.2.3. By Application
    • 11.2.4. By End-User
    • 11.2.5. By Country
    • 11.2.6. Key Takeaways
  • 11.3. South America: Country Analysis
    • 11.3.1. Brazil Machine Learning as a Service 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 Organization Size
        • 11.3.1.2.3. By Application
        • 11.3.1.2.4. By End-User
    • 11.3.2. Argentina Machine Learning as a Service 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 Organization Size
        • 11.3.2.2.3. By Application
        • 11.3.2.2.4. By End-User
    • 11.3.3. Colombia Machine Learning as a Service 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 Organization Size
        • 11.3.3.2.3. By Application
        • 11.3.3.2.4. By End-User

12. Market Dynamics

  • 12.1. Drivers
    • 12.1.1. Increase demand for cloud computing
    • 12.1.2. Growth associate with cognitive computing & AI
    • 12.1.3. Rise in adoption of analytics solutions
  • 12.2. Challenges
    • 12.2.1. Lack of skilled resources
    • 12.2.2. Lacking infrastructure

13. Market Trends and Developments

  • 13.1. Increasing customer facing activities
  • 13.2. Smarter back office & operations
  • 13.3. Growing use of machine learning in retail sector
  • 13.4. Mergers & Acquisitions
  • 13.5. Exponential growth of big data

14. Company Profiles

  • 14.1. Google Inc
    • 14.1.1. Company Overview
    • 14.1.2. Product Portfolio
    • 14.1.3. SWOT Analysis
    • 14.1.4. Key Personals
    • 14.1.5. Recent Developments/Updates
  • 14.2. SAS Institute Inc
    • 14.2.1. Company Overview
    • 14.2.2. Product Portfolio
    • 14.2.3. SWOT Analysis
    • 14.2.4. Key Personals
    • 14.2.5. Recent Developments/Updates
  • 14.3. Fair Isaac Corporation
    • 14.3.1. Company Overview
    • 14.3.2. Product Portfolio
    • 14.3.3. SWOT Analysis
    • 14.3.4. Key Personals
    • 14.3.5. Recent Developments/Updates
  • 14.4. Hewlett Packard Enterprise Development LP
    • 14.4.1. Company Overview
    • 14.4.2. Product Portfolio
    • 14.4.3. SWOT Analysis
    • 14.4.4. Key Personals
    • 14.4.5. Recent Developments/Updates
  • 14.5. Yottamine Analytics Inc.
    • 14.5.1. Company Overview
    • 14.5.2. Product Portfolio
    • 14.5.3. SWOT Analysis
    • 14.5.4. Key Personals
    • 14.5.5. Recent Developments/Updates
  • 14.6. Amazon Web Services
    • 14.6.1. Company Overview
    • 14.6.2. Product Portfolio
    • 14.6.3. SWOT Analysis
    • 14.6.4. Key Personals
    • 14.6.5. Recent Developments/Updates
  • 14.7. BigML, Inc.
    • 14.7.1. Company Overview
    • 14.7.2. Product Portfolio
    • 14.7.3. SWOT Analysis
    • 14.7.4. Key Personals
    • 14.7.5. Recent Developments/Updates
  • 14.8. Microsoft Corporation
    • 14.8.1. Company Overview
    • 14.8.2. Product Portfolio
    • 14.8.3. SWOT Analysis
    • 14.8.4. Key Personals
    • 14.8.5. Recent Developments/Updates
  • 14.9. IBM Corporation
    • 14.9.1. Company Overview
    • 14.9.2. Product Portfolio
    • 14.9.3. SWOT Analysis
    • 14.9.4. Key Personals
    • 14.9.5. Recent Developments/Updates
  • 14.10. Broadcom Corporation
    • 14.10.1. Company Overview
    • 14.10.2. Product Portfolio
    • 14.10.3. SWOT Analysis
    • 14.10.4. Key Personals
    • 14.10.5. Recent Developments/Updates

15. Strategic Recommendations

  • 15.1. Use sophisticated algorithms for data utilizing
  • 15.2. Use customer churn modelling

16. About Us & Disclaimer