The machine learning as a service market would grow at a CAGR of 39.3% over the predicted time frame. The market is expected to increase in value from US$ 21.55 Bn in 2022 to US$ 305.62 Bn in 2030.
The on machine learning as a service Market, which provides a business strategy, research & development activities, concise outline of the market valuation, valuable insights pertaining to market share, size, supply chain analysis, competitive landscape and regional proliferation of this industry.
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Report Scope of the Machine Learning as a Service Market
| Report Coverage | Details |
| Market Size in 2022 | USD 21.55 Billion |
| Market Size by 2030 | USD 305.62 Billion |
| Growth Rate from 2022 to 2030 | CAGR of 39.3% |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Segments Covered | Component, Organization Size, Application, Industry Vertical, Geography |
A recent report provides crucial insights along with application based and forecast information in the Global Machine learning as a service Market. The report provides a comprehensive analysis of key factors that are expected to drive the growth of this market. This study also provides a detailed overview of the opportunities along with the current trends observed in the Machine learning as a service market.
A quantitative analysis of the industry is compiled for a period of 10 years in order to assist players to grow in the market. Insights on specific revenue figures generated are also given in the report, along with projected revenue at the end of the forecast period.
Companies and Manufacturers Covered
The study covers key players operating in the market along with prime schemes and strategies implemented by each player to hold high positions in the industry. Such a tough vendor landscape provides a competitive outlook of the industry, consequently existing as a key insight. These insights were thoroughly analysed and prime business strategies and products that offer high revenue generation capacities were identified. Key players of the global Machine learning as a service market are included as given below:
Machine learning as a service Market Key Players
- GOOGLE INC
- SAS INSTITUTE INC
- FICO
- HEWLETT PACKARD ENTERPRISE
- YOTTAMINE ANALYTICS
- AMAZON WEB SERVICES
- BIGML, INC
- MICROSOFT CORPORATION
- PREDICTRON LABS LTD
- IBM CORPORATION
Market Segments
By Component
- Solution
- Services
By Organization Size
- Small and Medium-Sized Enterprises
- Large Enterprises
By Application
- Marketing & Advertising
- Fraud Detection & Risk Management
- Computer vision
- Security & Surveillance
- Predictive analytics
- Natural Language Processing
- Augmented & Virtual Reality
- Others
By Industry Vertical
- BFSI
- IT & Telecom
- Automotive
- Healthcare
- Aerospace & Defense
- Retail
- Government
- Others
By Geography
- North America
- U.S.
- Canada
- Europe
- U.K.
- Germany
- France
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Malaysia
- Philippines
- Latin America
- Brazil
- Rest of Latin America
- Middle East & Africa (MEA)
Report Objectives
- To define, describe, and forecast the global machine learning as a service market based on product, and region
- To provide detailed information regarding the major factors influencing the growth of the market (drivers, opportunities, and industry-specific challenges)
- To strategically analyze micromarkets1 with respect to individual growth trends, future prospects, and contributions to the total market
- To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
- To forecast the size of market segments with respect to four main regions—North America, Europe, Asia Pacific and the Rest of the World (RoW)2
- To strategically profile key players and comprehensively analyze their product portfolios, market shares, and core competencies3
- To track and analyze competitive developments such as acquisitions, expansions, new product launches, and partnerships in the machine learning as a service market
Table of Content
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Machine Learning as a Service Market
5.1. COVID-19 Landscape: Machine Learning as a Service Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Machine Learning as a Service Market, By Component
8.1. Machine Learning as a Service Market, by Component, 2022-2030
8.1.1. Solution
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Machine Learning as a Service Market, By Organization Size
9.1. Machine Learning as a Service Market, by Organization Size e, 2022-2030
9.1.1. Small and Medium-Sized Enterprises
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Large Enterprises
9.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Machine Learning as a Service Market, By Application
10.1. Machine Learning as a Service Market, by Application, 2022-2030
10.1.1. Marketing & Advertising
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Fraud Detection & Risk Management
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Computer vision
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.4. Security & Surveillance
10.1.4.1. Market Revenue and Forecast (2017-2030)
10.1.5. Predictive analytics
10.1.5.1. Market Revenue and Forecast (2017-2030)
10.1.6. Natural Language Processing
10.1.6.1. Market Revenue and Forecast (2017-2030)
10.1.7. Augmented & Virtual Reality
10.1.7.1. Market Revenue and Forecast (2017-2030)
10.1.8. Others
10.1.8.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Machine Learning as a Service Market, By Industry Vertical
11.1. Machine Learning as a Service Market, by Industry Vertical, 2022-2030
11.1.1. BFSI
11.1.1.1. Market Revenue and Forecast (2017-2030)
11.1.2. IT & Telecom
11.1.2.1. Market Revenue and Forecast (2017-2030)
11.1.3. Automotive
11.1.3.1. Market Revenue and Forecast (2017-2030)
11.1.4. Healthcare
11.1.4.1. Market Revenue and Forecast (2017-2030)
11.1.5. Aerospace & Defense
11.1.5.1. Market Revenue and Forecast (2017-2030)
11.1.6. Retail
11.1.6.1. Market Revenue and Forecast (2017-2030)
11.1.7. Government
11.1.7.1. Market Revenue and Forecast (2017-2030)
11.1.8. Others
11.1.8.1. Market Revenue and Forecast (2017-2030)
Chapter 12. Global Machine Learning as a Service Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.1.3. Market Revenue and Forecast, by Application (2017-2030)
12.1.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.1.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.1.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.1.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.1.6.3. Market Revenue and Forecast, by Application (2017-2030)
12.1.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.2.3. Market Revenue and Forecast, by Application (2017-2030)
12.2.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.2.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.2.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.2.6.3. Market Revenue and Forecast, by Application (2017-2030)
12.2.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.2.7.3. Market Revenue and Forecast, by Application (2017-2030)
12.2.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.2.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.2.8.3. Market Revenue and Forecast, by Application (2017-2030)
12.2.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.3.3. Market Revenue and Forecast, by Application (2017-2030)
12.3.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.3.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.3.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.3.6.3. Market Revenue and Forecast, by Application (2017-2030)
12.3.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.3.7.3. Market Revenue and Forecast, by Application (2017-2030)
12.3.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.3.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.3.8.3. Market Revenue and Forecast, by Application (2017-2030)
12.3.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.4.3. Market Revenue and Forecast, by Application (2017-2030)
12.4.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.4.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.4.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.4.6.3. Market Revenue and Forecast, by Application (2017-2030)
12.4.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.7.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.4.7.3. Market Revenue and Forecast, by Application (2017-2030)
12.4.7.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Component (2017-2030)
12.4.8.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.4.8.3. Market Revenue and Forecast, by Application (2017-2030)
12.4.8.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.5.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.5.5.3. Market Revenue and Forecast, by Application (2017-2030)
12.5.5.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Component (2017-2030)
12.5.6.2. Market Revenue and Forecast, by Organization Size (2017-2030)
12.5.6.3. Market Revenue and Forecast, by Application (2017-2030)
12.5.6.4. Market Revenue and Forecast, by Industry Vertical (2017-2030)
Chapter 13. Company Profiles
13.1. GOOGLE INC
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. SAS INSTITUTE INC
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. FICO
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. HEWLETT PACKARD ENTERPRISE
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. YOTTAMINE ANALYTICS
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. AMAZON WEB SERVICES
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. BIGML, INC
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. MICROSOFT CORPORATION
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. PREDICTRON LABS LTD
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
13.10. IBM
13.10.1. Company Overview
13.10.2. Product Offerings
13.10.3. Financial Performance
13.10.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
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