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Automated Machine Learning Market by Automation Type (Data Processing, Feature Engineering, Modeling), Deployment (Cloud, On-premises), Application - Global Forecast 2024-2030

Publisher 360iResearch
Published Jan 15, 2024
Length 186 Pages
SKU # IRE18418661

Description

Automated Machine Learning Market by Automation Type (Data Processing, Feature Engineering, Modeling), Deployment (Cloud, On-premises), Application - Global Forecast 2024-2030


The Automated Machine Learning Market size was estimated at USD 1.63 billion in 2023 and expected to reach USD 2.21 billion in 2024, at a CAGR 35.70% to reach USD 13.88 billion by 2030.

FPNV Positioning Matrix

The FPNV Positioning Matrix is pivotal in evaluating the Automated Machine Learning Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Automated Machine Learning Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Key Company Profiles

The report delves into recent significant developments in the Automated Machine Learning Market, highlighting leading vendors and their innovative profiles. These include Aible, Inc., Akkio Inc., Altair Engineering Inc., Alteryx, Amazon Web Services, Inc., Automated Machine Learning Ltd., BigML, Inc., Databricks, Inc., Dataiku, DataRobot, Inc., Google LLC by Alphabet Inc., H2O.ai, Inc., Hewlett Packard Enterprise Company, InData Labs Group Limited, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, QlikTech International AB, Runai Labs Ltd., Salesforce, Inc., SAS Institute Inc., ServiceNow, Inc., SparkCognition, Inc., STMicroelectronics, Tata Consultancy Services Limited, TAZI AI, Tellius, Inc., Weidmuller Limited, Wolfram, and Yellow.ai.

Market Segmentation & Coverage

This research report categorizes the Automated Machine Learning Market to forecast the revenues and analyze trends in each of the following sub-markets:

Automation Type

Data Processing
  • Feature Engineering
  • Modeling
  • Visualization
  • Deployment

    Cloud
  • On-premises
  • Application

    Automotive, Transportations, and Logistics
  • Banking, Financial Services, and Insurance
  • Government & Defense
  • Healthcare & Life Sciences
  • It & Telecommunications
  • Media & Entertainment
  • Region

    Americas

    Argentina
  • Brazil
  • Canada
  • Mexico
  • United States

    California
  • Florida
  • Illinois
  • New York
  • Ohio
  • Pennsylvania
  • Texas
  • Asia-Pacific

    Australia
  • China
  • India
  • Indonesia
  • Japan
  • Malaysia
  • Philippines
  • Singapore
  • South Korea
  • Taiwan
  • Thailand
  • Vietnam
  • Europe, Middle East & Africa

    Denmark
  • Egypt
  • Finland
  • France
  • Germany
  • Israel
  • Italy
  • Netherlands
  • Nigeria
  • Norway
  • Poland
  • Qatar
  • Russia
  • Saudi Arabia
  • South Africa
  • Spain
  • Sweden
  • Switzerland
  • Turkey
  • United Arab Emirates
  • United Kingdom
    The report offers valuable insights on the following aspects:

    1. Market Penetration: It presents comprehensive information on the market provided by key players.
    2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
    3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
    4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
    5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
    The report addresses key questions such as:

    1. What is the market size and forecast of the Automated Machine Learning Market?
    2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Automated Machine Learning Market?
    3. What are the technology trends and regulatory frameworks in the Automated Machine Learning Market?
    4. What is the market share of the leading vendors in the Automated Machine Learning Market?
    5. Which modes and strategic moves are suitable for entering the Automated Machine Learning Market?


    Note: PDF & Excel + Online Access - 1 Year

    • Table of Contents

    186 Pages
    1. Preface
    1.1. Objectives of the Study
    1.2. Market Segmentation & Coverage
    1.3. Years Considered for the Study
    1.4. Currency & Pricing
    1.5. Language
    1.6. Limitations
    1.7. Assumptions
    1.8. Stakeholders
    2. Research Methodology
    2.1. Define: Research Objective
    2.2. Determine: Research Design
    2.3. Prepare: Research Instrument
    2.4. Collect: Data Source
    2.5. Analyze: Data Interpretation
    2.6. Formulate: Data Verification
    2.7. Publish: Research Report
    2.8. Repeat: Report Update
    3. Executive Summary
    4. Market Overview
    4.1. Introduction
    4.2. Automated Machine Learning Market, by Region
    5. Market Insights
    5.1. Market Dynamics
    5.1.1. Drivers
    5.1.1.1. Increasing demand for data-driven insights for decision-making
    5.1.1.2. Expanding democratization of machine learning capabilities
    5.1.2. Restraints
    5.1.2.1. Interpretability and transparency issues associated with AutoML platforms
    5.1.3. Opportunities
    5.1.3.1. Advancements in artificial intelligence (AI) and machine learning (ML) technologies
    5.1.3.2. Growing integration of AutoML with DevOps practices that enhance the development of machine learning models
    5.1.4. Challenges
    5.1.4.1. Security and privacy concerns of AutoML platforms
    5.2. Market Segmentation Analysis
    5.3. Market Trend Analysis
    5.4. Cumulative Impact of High Inflation
    5.5. Porter’s Five Forces Analysis
    5.5.1. Threat of New Entrants
    5.5.2. Threat of Substitutes
    5.5.3. Bargaining Power of Customers
    5.5.4. Bargaining Power of Suppliers
    5.5.5. Industry Rivalry
    5.6. Value Chain & Critical Path Analysis
    5.7. Regulatory Framework
    6. Automated Machine Learning Market, by Automation Type
    6.1. Introduction
    6.2. Data Processing
    6.3. Feature Engineering
    6.4. Modeling
    6.5. Visualization
    7. Automated Machine Learning Market, by Deployment
    7.1. Introduction
    7.2. Cloud
    7.3. On-premises
    8. Automated Machine Learning Market, by Application
    8.1. Introduction
    8.2. Automotive, Transportations, and Logistics
    8.3. Banking, Financial Services, and Insurance
    8.4. Government & Defense
    8.5. Healthcare & Life Sciences
    8.6. It & Telecommunications
    8.7. Media & Entertainment
    9. Americas Automated Machine Learning Market
    9.1. Introduction
    9.2. Argentina
    9.3. Brazil
    9.4. Canada
    9.5. Mexico
    9.6. United States
    10. Asia-Pacific Automated Machine Learning Market
    10.1. Introduction
    10.2. Australia
    10.3. China
    10.4. India
    10.5. Indonesia
    10.6. Japan
    10.7. Malaysia
    10.8. Philippines
    10.9. Singapore
    10.10. South Korea
    10.11. Taiwan
    10.12. Thailand
    10.13. Vietnam
    11. Europe, Middle East & Africa Automated Machine Learning Market
    11.1. Introduction
    11.2. Denmark
    11.3. Egypt
    11.4. Finland
    11.5. France
    11.6. Germany
    11.7. Israel
    11.8. Italy
    11.9. Netherlands
    11.10. Nigeria
    11.11. Norway
    11.12. Poland
    11.13. Qatar
    11.14. Russia
    11.15. Saudi Arabia
    11.16. South Africa
    11.17. Spain
    11.18. Sweden
    11.19. Switzerland
    11.20. Turkey
    11.21. United Arab Emirates
    11.22. United Kingdom
    12. Competitive Landscape
    12.1. FPNV Positioning Matrix
    12.2. Market Share Analysis, By Key Player
    12.3. Competitive Scenario Analysis, By Key Player
    13. Competitive Portfolio
    13.1. Key Company Profiles
    13.1.1. Aible, Inc.
    13.1.2. Akkio Inc.
    13.1.3. Altair Engineering Inc.
    13.1.4. Alteryx
    13.1.5. Amazon Web Services, Inc.
    13.1.6. Automated Machine Learning Ltd.
    13.1.7. BigML, Inc.
    13.1.8. Databricks, Inc.
    13.1.9. Dataiku
    13.1.10. DataRobot, Inc.
    13.1.11. Google LLC by Alphabet Inc.
    13.1.12. H2O.ai, Inc.
    13.1.13. Hewlett Packard Enterprise Company
    13.1.14. InData Labs Group Limited
    13.1.15. Intel Corporation
    13.1.16. International Business Machines Corporation
    13.1.17. Microsoft Corporation
    13.1.18. Oracle Corporation
    13.1.19. QlikTech International AB
    13.1.20. Runai Labs Ltd.
    13.1.21. Salesforce, Inc.
    13.1.22. SAS Institute Inc.
    13.1.23. ServiceNow, Inc.
    13.1.24. SparkCognition, Inc.
    13.1.25. STMicroelectronics
    13.1.26. Tata Consultancy Services Limited
    13.1.27. TAZI AI
    13.1.28. Tellius, Inc.
    13.1.29. Weidmuller Limited
    13.1.30. Wolfram
    13.1.31. Yellow.ai
    13.2. Key Product Portfolio
    14. Appendix
    14.1. Discussion Guide
    14.2. License & Pricing
    FIGURE 1. AUTOMATED MACHINE LEARNING MARKET RESEARCH PROCESS
    FIGURE 2. AUTOMATED MACHINE LEARNING MARKET SIZE, 2023 VS 2030
    FIGURE 3. AUTOMATED MACHINE LEARNING MARKET SIZE, 2018-2030 (USD MILLION)
    FIGURE 4. AUTOMATED MACHINE LEARNING MARKET SIZE, BY REGION, 2023 VS 2030 (%)
    FIGURE 5. AUTOMATED MACHINE LEARNING MARKET SIZE, BY REGION, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 6. AUTOMATED MACHINE LEARNING MARKET DYNAMICS
    FIGURE 7. AUTOMATED MACHINE LEARNING MARKET SIZE, BY AUTOMATION TYPE, 2023 VS 2030 (%)
    FIGURE 8. AUTOMATED MACHINE LEARNING MARKET SIZE, BY AUTOMATION TYPE, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 9. AUTOMATED MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT, 2023 VS 2030 (%)
    FIGURE 10. AUTOMATED MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 11. AUTOMATED MACHINE LEARNING MARKET SIZE, BY APPLICATION, 2023 VS 2030 (%)
    FIGURE 12. AUTOMATED MACHINE LEARNING MARKET SIZE, BY APPLICATION, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 13. AMERICAS AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
    FIGURE 14. AMERICAS AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 15. UNITED STATES AUTOMATED MACHINE LEARNING MARKET SIZE, BY STATE, 2023 VS 2030 (%)
    FIGURE 16. UNITED STATES AUTOMATED MACHINE LEARNING MARKET SIZE, BY STATE, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 17. ASIA-PACIFIC AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
    FIGURE 18. ASIA-PACIFIC AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 19. EUROPE, MIDDLE EAST & AFRICA AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
    FIGURE 20. EUROPE, MIDDLE EAST & AFRICA AUTOMATED MACHINE LEARNING MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
    FIGURE 21. AUTOMATED MACHINE LEARNING MARKET, FPNV POSITIONING MATRIX, 2023
    FIGURE 22. AUTOMATED MACHINE LEARNING MARKET SHARE, BY KEY PLAYER, 2023

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