by Precedence Research a new report on machine learning as a service market size, share, growth, industry trends, and forecast 2030, covering various industry elements and growth trends helpful for predicting the market’s future. The global machine learning as a service market size was valued at US$ 15.47 billion in 2021. The global machine learning as a service market is projected to reach US$ 305.62 billion by 2030, registering a compound annual growth rate (CAGR) of 39.3% during the forecast period from 2022 to 2030.
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The global machine learning as a service market report offers various segments analysis by size, trends, growth factors, opportunities and key country outlook to 2030. The report offers a detailed analysis and information as per machine learning as a service, market segments helping our readers to get a comprehensive overview of the global market. Several players are planning to focus on developing cost-effective products or services, aiming to maintain a strong foothold in the market.
Machine Learning as a Service Market Report Scope
| 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 |
The company profiling of leading market players is included this report with Porter’s five forces analysis and Value Chain analysis. Further, the strategies exercised by the companies for expansion of business through mergers, acquisitions, and other business development measures are discussed in the report. The financial parameters which are assessed include the sales, profits and the overall revenue generated by the key players of Market.
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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]
Key Questions are
- What are the key factors influencing the machine learning as a service market in each region?
- How much value will the global market generate by the end of the forecast period?
- What will be the CAGR of the global market between 2022 and 2030?
- What would be the Y-o-Y growth trend of the global market between 2022 and 2030?
- What is the future scope and current trends in technologies of the global market?
- What is the revenue of the global market based on segments?
- Which key strategies are used by top players of the global market?
- Which are the leading companies in the global market?
- What are the essential strategies by key stakeholders in the market to expand their geographic presence?
- What are the major advancements witnessed in the global market?
Research Objectives and Research Approach
The comprehensive report on the global machine learning as a service market begins with an overview, followed by the scope and objectives of the study. The report provides detailed explanation of the objectives behind this study and key vendors and distributors operating in the market and regulatory scenario for approval of products. Following this, the report provides detailed explanation of objectives of this study and laid down by accredited agencies in the purview of research in the global machine learning as a service market.
It is followed by market introduction, market dynamics, and an overview of the global market, which includes analysis of market drivers, restraints, and trends pertaining to the global market. Furthermore, Y-o-Y growth analysis with elaborated insights has been provided in order to understand the Y-o-Y growth trend of the global market.
For reading comprehensibility, the report has been compiled in a chapter-wise layout, with each section divided into smaller sections. The report comprises an exhaustive collection of graphs and tables that are appropriately interspersed. Pictorial representation of actual and projected values of key segments is visually appealing to readers. This also allows comparison of the market shares of key segments in the past and at the end of the forecast period.
The report analyzes the global machine learning as a service market in terms of type, application, region and others. Key segments under each criteria are studied at length, and the market share for each of these at the end of 2030 has also been provided. Such valuable insights enable market stakeholders in making informed business decisions for investment in the global market.
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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