Machine Learning as a Service (MLaaS) Market 2023 – 2030 By Organization Size (Small and Medium Enterprises, Large Enterprises), End User (IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI)Application ( Marketing and Advertisement, Predictive Maintenance, Automated Network Management, Fraud Detection and Risk Analytics) -Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional Footprints by MarketDigits
Industry : Information Technology | Pages : 149 Pages | Published On : Jun 2023
The Machine Learning as a Service (MLaaS) Market size is estimated to grow from USD XX Billion in 2020 to USD XX Billion by 2027, growing at a CAGR of 43% during the forecast year from 2021 to 2027.
The latest report on Machine Learning as a Service (MLaaS) Market understands market size estimates, forecasts, market shares, competition analysis, along with industry trends of Machine Learning as a Service with emphasis on market timelines and technology roadmaps analysis.
The Machine Learning as a Service (MLaaS) Market is segmented by component, service, organisation size, application and region. The research covers the current and historic Machine Learning as a Service (MLaaS) Market size and its growth trend with company outline of Key players /manufacturers: Microsoft Corporation, IBM Corporation, Google LLC, SAS Institute Inc., Fair Isaac Corporation (FICO), Hewlett Packard Enterprise Company, Yottamine Analytics LLC, Amazon Web Services Inc., BigML Inc., Iflowsoft Solutions Inc., PurePredictive Inc., Sift Science Inc., H2O.ai Inc. among others
Analysis of the global market with special focus on high growth application in each vertical and fast-growing market segments. It includes detailed competitive landscape with identification of the key players with respect to each type of market, in-depth market share analysis with individual revenue, market shares, and top players rankings. Impact analysis of the market dynamics with factors currently driving and restraining the growth of the market, along with their impact in the short, medium, and long-term landscapes. Competitive intelligence from the company profiles, key player strategies, game-changing developments such as product launches and acquisitions.
The objective of this study is to identify the market opportunities and estimate market size by segments and countries for last few years and to forecast the values to the next five years. The report incorporates both the qualitative and quantitative aspects of the industry with respect to each of the regions and countries involved in the study. The report also covers qualitative analysis on the market, by incorporating complete pricing and cost analysis of components & products, Porter’s analysis and PEST (Political, Economic, Social & Technological factor) analysis of the market. The report also profiles all major companies active in this field.
Market Analysis and Insights: Machine Learning as a Service (MLaaS) Market Analysis & Insights
Market Scope and Market Size
Machine Learning as a Service (MLaaS) Market is segmented by component, service, organisation size, application and region. Players, stakeholders, and other participants in the global Machine Learning as a Service (MLaaS) Market will be able to gain a strong position as this report will surely benefit their marketing strategies. The market analysis focuses on revenue and forecast by region/countries and by application in terms of revenue and forecast for the period 2016-2027.
Report further studies the market development status and future and Machine Learning as a Service (MLaaS) Market trend across the world. Also, it splits Machine Learning as a Service (MLaaS) Market by component, service, organisation size, application and region to deep dive research and reveals market profile and prospects.
Major Classifications are as follows:
- Software Tools
- Data Storage and Archiving
- Modeler and Processing
- Multiplayer Perceptron (MLP)
- K-Nearest Neighbors (KMN)
- Support Vector Regressions (SVR)
- Others(Decision Tree(DT),
- Principle Component Analysis(PCA), Principle Component Analysis(PCA)
- k- Means Algorithms, Reinforcement Learning, and Bayesian Statistics))
- Cloud and Web-based Application Programming Interface (APIs)
- Others (Model Validator, Decision Report/Predictor/Training, and Report Storage)
- Professional Services
- Managed Services
By Enterprise Applications:
- Marketing and Advertising.
- Risk Analytics and Fraud Detection
- Predictive Maintenance (Pattern recognition & generation, anomaly detection)
- Augmented Reality (Pattern recognition & generation, object recognition, automated simulation, prediction/recommendation)
- Network Analytics and Automated Traffic Management (SDN and NFV/ automated traffic generation/ etc.)
By Organization Size:
- Large Enterprises
- North America
- Rest of Europe
- Asia-Pacific (APAC)
- Rest of APAC
- Rest of the World (RoW)
- Middle East
- South America
Reason to purchase this Machine Learning as a Service Market Report:
- Determine prospective investment areas based on a detailed trend analysis of the global Machine Learning as a Service market over the next years.
- Gain an in-depth understanding of the underlying factors driving demand for different and Machine Learning as a Service market segments in the top spending countries across the world and identify the opportunities offered by each of them.
- Strengthen your understanding of the market in terms of demand drivers, industry trends, and the latest technological developments, among others.
- Identify the major channels that are driving the global Machine Learning as a Service market, providing a clear picture of future opportunities that can be tapped, and resulting in revenue expansion.
- Channelize resources by focusing on the ongoing programs that are being undertaken by the different countries within the global Machine Learning as a Service market.
- Make correct business decisions based on a thorough analysis of the total competitive landscape of the sector with detailed profiles of the top Machine Learning as a Service market providers around the world which include information about their products, alliances, recent contract wins and financial analysis wherever available.
Table of Contents:
1. EXECUTIVE SUMMARY 2. INTRODUCTION 2.1. Key Takeaways 2.2. Report Description 2.3. Market Scope & Definition 2.4. Stakeholders 2.5. Research Methodology 2.5.1. Market Size 2.5.2. Key Data Points From Primary Sources 2.5.3. Key Data Points From Secondary Sources 2.5.4. List Of Primary Sources 2.5.5. List Of Secondary Sources 3. MARKET OVERVIEW 3.1. Industry Segmentation 3.2. Market Trends Analysis 3.3. Major Funding & Investments 3.4. Market Dynamics 3.4.1. Drivers 3.4.2. Restraints 3.4.3. Opportunities 3.5. Value Chain Analysis 3.6. Pricing Analysis 4. IMPACT OF COVID-19 ON MACHINE LEARNING AS A SERVICE MARKET 4.1. Impact Of Covid-19 On Machine Learning as a Service Market, By Component 4.2. Impact Of Covid-19 On Machine Learning as a Service Market, By Service 4.3. Impact Of Covid-19 On Machine Learning as a Service Market, By Organisation size 4.4. Impact Of Covid-19 On Machine Learning as a Service Market, By Application 4.5. Impact of Covid-19 On Machine Learning as a Service Market, By Geography 5. MACHINE LEARNING AS A SERVICE MARKET, BY COMPONENT 5.1. Introduction 5.2. Software Tools 5.3. Data Storage and Archiving 5.3.1. Modeler and Processing 5.3.2. Multiplayer Perceptron (MLP) 5.3.3. K-Nearest Neighbors (KMN) 5.3.4. Support Vector Regressions (SVR) 5.3.5. Others(Decision Tree(DT), 22.214.171.124. Principle Component Analysis(PCA), Principle Component Analysis(PCA) 126.96.36.199. k- Means Algorithms, Reinforcement Learning, and Bayesian Statistics)) 5.4. Cloud and Web-based Application Programming Interface (APIs) 5.5. Others (Model Validator, Decision Report/Predictor/Training, and Report Storage) 6. MACHINE LEARNING AS A SERVICE MARKET, BY SERVICE 6.1. Introduction 6.2. Professional Services 6.3. Managed Services 7. MACHINE LEARNING AS A SERVICE MARKET, BY ORGANISATION SIZE 7.1. Introduction 7.2. SMEs 7.3. Large Enterprises 8. MACHINE LEARNING AS A SERVICE MARKET, BY APPLICATION 8.1. Introduction 8.2. Marketing and Advertising. 8.3. Risk Analytics and Fraud Detection 8.4. Predictive Maintenance (Pattern recognition & generation, anomaly detection) 8.5. Augmented Reality (Pattern recognition & generation, object recognition, automated simulation, prediction/recommendation) 8.6. Network Analytics and Automated Traffic Management (SDN and NFV/ automated traffic generation/ etc.) 8.7. Others 9. MACHINE LEARNING AS A SERVICE MARKET, BY GEOGRAPHY 9.1. Introduction 9.2. North America 9.2.1. U.S. 9.2.2. Canada 9.3. Europe 9.3.1. Germany 9.3.2. U.K. 9.3.3. France 9.3.4. Rest of Europe 9.4. Asia Pacific 9.4.1. China 9.4.2. Japan 9.4.3. India 9.4.4. Rest Of Asia Pacific 9.5. Rest of the World 9.5.1. Middle East 9.5.2. Africa 9.5.3. Latin America 10. COMPETITIVE ANALYSIS 10.1. Introduction 10.2. Top Companies Ranking 10.3. Market Share Analysis 10.4. Recent Developments 10.4.1. New Product Launch 10.4.2. Mergers & Acquisitions 10.4.3. Collaborations, Partnerships & Agreements 10.4.4. Rewards & Recognition 11. COMPANY PROFILES 11.1. Microsoft Corporation 11.2. IBM Corporation 11.3. Google LLC 11.4. SAS Institute Inc. 11.5. Fair Isaac Corporation (FICO) 11.6. Hewlett Packard Enterprise Company 11.7. Yottamine Analytics LLC 11.8. Amazon Web Services Inc. 11.9. BigML Inc. 11.10. Iflowsoft Solutions Inc. 11.11. PurePredictive Inc. 11.12. Sift Science Inc. 11.13. H2O.ai Inc.
Table and Figures
At MarketDigits, we take immense pride in our 360° Research Methodology, which serves as the cornerstone of our research process. It represents a rigorous and comprehensive approach that goes beyond traditional methods to provide a holistic understanding of industry dynamics.
This methodology is built upon the integration of all seven research methodologies developed by MarketDigits, a renowned global research and consulting firm. By leveraging the collective strength of these methodologies, we are able to deliver a 360° view of the challenges, trends, and issues impacting your industry.
The first step of our 360° Research Methodology™ involves conducting extensive primary research, which involves gathering first-hand information through interviews, surveys, and interactions with industry experts, key stakeholders, and market participants. This approach enables us to gather valuable insights and perspectives directly from the source.
Secondary research is another crucial component of our methodology. It involves a deep dive into various data sources, including industry reports, market databases, scholarly articles, and regulatory documents. This helps us gather a wide range of information, validate findings, and provide a comprehensive understanding of the industry landscape.
Furthermore, our methodology incorporates technology-based research techniques, such as data mining, text analytics, and predictive modelling, to uncover hidden patterns, correlations, and trends within the data. This data-driven approach enhances the accuracy and reliability of our analysis, enabling us to make informed and actionable recommendations.
In addition, our analysts bring their industry expertise and domain knowledge to bear on the research process. Their deep understanding of market dynamics, emerging trends, and future prospects allows for insightful interpretation of the data and identification of strategic opportunities.
To ensure the highest level of quality and reliability, our research process undergoes rigorous validation and verification. This includes cross-referencing and triangulation of data from multiple sources, as well as peer reviews and expert consultations.
The result of our 360° Research Methodology is a comprehensive and robust research report that empowers you to make well-informed business decisions. It provides a panoramic view of the industry landscape, helping you navigate challenges, seize opportunities, and stay ahead of the competition.
In summary, our 360° Research Methodology is designed to provide you with a deep understanding of your industry by integrating various research techniques, industry expertise, and data-driven analysis. It ensures that every business decision you make is based on a well-triangulated and comprehensive research experience.
- Tailored advice to Drive your Performance
- Product Planning Strategy
- New Product Stratergy
- Expanded Research Scope
- Comprehensive Research
- Strategic Consulting
- Provocative and pragmatic
- Accelerate Revenue & Growth
- Evaluate the competitive landscape
- Optimize your partner network
- Analyzing industries
- Mapping trends
- Strategizing growth
- Implementing plans
Covered Key Topics
Market Growth Drivers
Leading Market Players
Company Market Share
Market Size and Growth Rate
Market Trend and Technological