by [150+ Pages Report] As per the latest Research and survey report issued by Precedence Research, the global machine learning as a service market was valued at around USD 15.47 billion in 2021 and is expected to register revenues worth USD 305.62 billion by the end of 2030, growing at an exceptional CAGR of approximately 39.3% between 2022 and 2030.
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Machine Learning as a Service Market Report Scope
A recent study by Precedence Research on the machine learning as a service market offers a forecast for 2022 and 2030. The study analyzes crucial trends that are currently determining the growth of the machine learning as a service market. This report explicates on vital dynamics such as the drivers, restraints, and opportunities for key market players, along with key stakeholders as well as emerging players associated with the manufacturing of machine learning as a service. The study also provides the dynamics that are responsible for influencing the future status of the machine learning as a service market over the forecast period.
A detailed assessment of the machine learning as a service market value chain analysis, business execution, and supply chain analysis across regional markets has been covered in the report. A list of prominent companies operating in the machine learning as a service market along with their product portfolio enhances the reliability of this comprehensive research study.
Competition Landscape
The report has engulfed a chapter on the global machine learning as a service market’s competitive landscape, which provides detailed analysis and insights on companies offering machine learning as a service. Profiles of key companies, along with a strategic overview of their M&A and expansion plans across geographies, have been delivered in this chapter. This chapter is priceless for report readers, as its enables them in gauging their growth potential in the market and implement key strategies for extending their market reach.
This chapter offers key recommendations for both new and existing market participants, enabling them to emerge sustainably and profitably. Intelligence on the market players has been delivered on the basis of their product overview, SWOT analysis, key developments, key financials and company overview. Occupancy of these market participants has been tracked by the report and portrayed via an intensity map.
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Some of the Prominent Players in the Machine Learning as a Service Market Include:
- GOOGLE INC
- SAS INSTITUTE INC
- FICO
- HEWLETT PACKARD ENTERPRISE
- YOTTAMINE ANALYTICS
- AMAZON WEB SERVICES
- BIGML, INC
- MICROSOFT CORPORATION
- PREDICTRON LABS LTD
- IBM CORPORATION
Machine Learning as a Service Market Segmentation
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
Regional Segmentation
- Asia-Pacific [China, Southeast Asia, India, Japan, Korea, Western Asia]
- Europe [Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
- North America [United States, Canada, Mexico]
- South America [Brazil, Argentina, Columbia, Chile, Peru]
- Middle East & Africa [GCC, North Africa, South Africa]
Regional Analysis
The research report includes a detailed study of regions of North America, Europe, China, Japan and Rest of the World. The report has been curated after observing and studying various factors that determine regional growth such as economic, environmental, social, technological, and political status of the particular region. Analysts have studied the data of revenue and manufacturers of each region. This section analyses region-wise revenue and volume for the forecast period of 2022 to 2030. These analyses will help the reader to understand the potential worth of investment in a particular region.
The report provides in-depth segment analysis of the global machine learning as a service market, thereby providing valuable insights at macro as well as micro levels. Analysis of major countries, which hold growth opportunities or account for significant share has also been included as part of geographic analysis of the machine learning as a service market.
The report includes country-wise and region-wise market size for the period 2022-2030. It also includes market size and forecast by segments in terms of production capacity, price and revenue for the period 2022-2030.
Why should you invest in this report?
If you are aiming to enter the global machine learning as a service market, this report is a comprehensive guide that provides crystal clear insights into this niche market. All the major application areas for machine learning as a service are covered in this report and information is given on the important regions of the world where this market is likely to boom during the forecast period of 2022-2030 so that you can plan your strategies to enter this market accordingly.
Besides, through this report, you can have a complete grasp of the level of competition you will be facing in this hugely competitive market and if you are an established player in this market already, this report will help you gauge the strategies that your competitors have adopted to stay as market leaders in this market. For new entrants to this market, the voluminous data provided in this report is invaluable.
Table of Contents
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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