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自动化机器学习市场规模和份额分析：按交付形式、部署类型、公司规模、应用、行业 - 到 2030 年的全球行业需求预测
市场调查报告书
商品编码
1222230

自动化机器学习市场规模和份额分析：按交付形式、部署类型、公司规模、应用、行业 - 到 2030 年的全球行业需求预测

Automated Machine Learning Market Size and Share Analysis By Offering, Deployment Type, Enterprise Size, Application, Industry - Global Industry Demand Forecast to 2030
出版日期: | 出版商: Prescient & Strategic Intelligence | 英文 221 Pages | 商品交期: 2-3个工作天内

价格

全球自动化机器学习市场规模预计将从 2022 年的 6.31 亿美元增长到 2030 年的 154.993 亿美元，从 2022 年到 2030 年的复合年增长率为 49.2%。我来了。 推动市场发展的关键因素包括对有效欺诈检测解决方案的需求不断增长，以及对个性化产品推荐的需求不断增长。

本报告研究和分析了全球自动化机器学习市场，提供了市场动态、按细分市场和地区划分的市场分析、竞争格局以及主要参与者概况等信息。

内容

第一章研究背景

第二章研究方法论

第 3 章执行摘要

第四章介绍

  • 市场细分定义
    • 按规定形式
      • 平台
      • 服务
    • 按部署类型
      • 本地
      • 云
    • 按公司规模
      • 大公司
      • 中小企业
    • 通过使用
      • 欺诈检测
      • 销售和营销管理
      • 体检
      • 传输优化
      • 其他
    • 按行业
      • BFSI
      • IT/通讯
      • 医疗保健
      • 政府
      • 零售
      • 製造业
      • 其他
  • 市场动态
    • 趋势
      • 对基于云的平台的偏好不断上升
    • 司机
      • 对高效欺诈检测解决方案的需求不断增加
      • 对个性化产品推荐的需求不断增长
      • 预测性潜在客户评分的重要性与日俱增
      • 驱动因素对市场预测的影响分析
    • 约束因素
      • 缺乏熟练的技术人员
      • 分析制约因素对市场预测的影响
    • 机会
      • 不断发展的医疗保健行业
      • 有效分类的重要性与日俱增
  • COVID-19 对自动化机器学习市场的影响
  • 波特的五力分析
  • 自动化机器学习的优势
  • 价值链分析

第 5 章全球市场规模和预测

  • 按规定形式
    • 按服务
  • 按部署类型
  • 按公司规模
  • 通过使用
  • 按行业
  • 按地区

第六章北美市场规模及预测

第7章欧洲市场规模及预测

第八章亚太市场规模及预测

第 9 章拉丁美洲市场规模和预测

第 10 章中东和非洲市场规模和预测

第11章竞争格局

  • 主要公司名单
  • 市场占有率指数（基于受欢迎程度和网络流量）
  • 主要公司的近期活动
  • 主要公司的战略发展
    • 併购
    • 伙伴关係
    • 推出产品/服务
    • 其他

第12章公司简介

  • DataRobot Inc.
  • H2O.ai Inc.
  • dotData Inc.
  • EdgeVerve Systems Limited
  • Amazon Web Services Inc.
  • Squark
  • Qlik Technologies Inc.
  • SAS Institute Inc.
  • Microsoft Corporation
  • Determined.ai Inc.
  • JADBio - Gnosis DA S.A.
  • BigML Inc.
  • Splunk Inc.
  • Tellius Inc.
  • Aible Inc.
  • International Business Machines（IBM）Corporation
  • Google LLC
  • RapidMiner
  • TAZI AI
  • MLJAR Sp. z o. o.
  • Akkio Inc.
  • Enhencer LLC
  • Dataiku

第13章 附录

Product Code: 11843

In 2022, the automated machine learning market size stood at USD 631.0 million, which is projected to witness a 49.2% CAGR during 2022-2030, reaching USD 15,499.3 million by 2030 as per P&S Intelligence.

The major factors accountable for the development of the market include the growing demand for effective fraud-finding solutions and the rising need for personalized product recommendations.

In 2022, The platform category generated the larger revenue share, of 73%, on the basis of offering. This growth can be credited to the growing acceptance of such platforms across all verticals for operational cost reduction, customer service improvement, and fraud deduction.

Furthermore, the pandemic helped in lifting digital transformation in nearly every industry, like healthcare, manufacturing, and BFSI, which is contributing to the adoption of this technology.

In 2022, The cloud category held the higher market share, on the basis of deployment type. This is due to the advanced flexibility and scalability of cloud-based automated machine-learning channels, which clients can modify according to their needs. Furthermore, as the cloud lessens the infrastructure and operational expenses, a huge number of businesses are more and more accepting cloud-based solutions.

On the basis of application, the sales and marketing management category are set to witness the fastest growth in the coming years. this can be owed to the huge number of businesses are utilizing such platforms in order to gain insights into buyer emotion and offer content personalization, customer segmentation, customer engagement, and lead scoring.

On the basis of industry, the healthcare category is set to experience the highest growth in the coming years. This is due to the hike in the demand for ML by the healthcare sector for the early recognition of illnesses, training, research and treating patients fast and efficiently, while reducing money, time, and resources.

In 2022, North America accounted for the highest revenue in the automated machine learning market. this can be credited to the advanced information technology infrastructure, prosperous BFSI, IT & telecom, the existence of main AutoML platform providers, and the healthcare sector are the key factors boosting the market growth in the continent.

The APAC market is projected to experience the fastest growth in the forecast period. This is because of snowballing spending on the IT infrastructure, a growing number of government efforts for the growth of AI technologies, and smooth economic development.

Additionally, APAC nations are preferring destinations for IT outsourcing. Credited to this, IT businesses are obtaining significant requests for application development, which fuels the growth of the market.

Thus, the growing demand for effective fraud-finding solutions and the rising need for personalized product recommendations will drive the automated machine-learning industry in the future.

Table of Contents

Chapter 1. Research Background

  • 1.1. Research Objectives
  • 1.2. Market Definition
  • 1.3. Research Scope
    • 1.3.1. Market Segmentation by Offering
    • 1.3.2. Market Segmentation by Deployment Type
    • 1.3.3. Market Segmentation by Enterprise Size
    • 1.3.4. Market Segmentation by Application
    • 1.3.5. Market Segmentation by Industry
    • 1.3.6. Market Segmentation by Region
    • 1.3.7. Analysis Period
    • 1.3.8. Market Data Reporting Unit
      • 1.3.8.1. Value
  • 1.4. Key Stakeholders

Chapter 2. Research Methodology

  • 2.1. Secondary Research
    • 2.1.1. Paid
    • 2.1.2. Unpaid
    • 2.1.3. P&S Intelligence Database
  • 2.2. Primary Research
    • 2.2.1. Breakdown of Primary Research Respondents
      • 2.2.1.1. By region
      • 2.2.1.2. By industry participant
      • 2.2.1.3. By company type
  • 2.3. Market Size Estimation
  • 2.4. Data Triangulation
  • 2.5. Currency Conversion Rates
  • 2.6. Assumptions for the Study

Chapter 3. Executive Summary

Chapter 4. Introduction

  • 4.1. Definition of Market Segments
    • 4.1.1. By Offering
      • 4.1.1.1. Platform
      • 4.1.1.2. Service
        • 4.1.1.2.1. Professional
        • 4.1.1.2.2. Managed
    • 4.1.2. By Deployment Type
      • 4.1.2.1. On-premises
      • 4.1.2.2. Cloud
    • 4.1.3. By Enterprise Size
      • 4.1.3.1. Large enterprise
      • 4.1.3.2. SME
    • 4.1.4. By Application
      • 4.1.4.1. Fraud detection
      • 4.1.4.2. Sales & marketing management
      • 4.1.4.3. Medical testing
      • 4.1.4.4. Transport optimization
      • 4.1.4.5. Others
    • 4.1.5. By Industry
      • 4.1.5.1. BFSI
      • 4.1.5.2. IT & telecom
      • 4.1.5.3. Healthcare
      • 4.1.5.4. Government
      • 4.1.5.5. Retail
      • 4.1.5.6. Manufacturing
      • 4.1.5.7. Others
  • 4.2. Market Dynamics
    • 4.2.1. Trends
      • 4.2.1.1. Increasing preference for cloud-based platforms
    • 4.2.2. Drivers
      • 4.2.2.1. Increasing demand for efficient fraud detection solutions
      • 4.2.2.2. Growing need for personalized product recommendations
      • 4.2.2.3. Rising importance of predictive lead scoring
      • 4.2.2.4. Impact analysis of drivers on market forecast
    • 4.2.3. Restraints
      • 4.2.3.1. Shortage of technologically skilled personnel
      • 4.2.3.2. Impact analysis of restraints on market forecast
    • 4.2.4. Opportunities
      • 4.2.4.1. Growing healthcare industry
      • 4.2.4.2. Rising importance of effective product assortment
  • 4.3. Impact of COVID-19 on AutoML Market
  • 4.4. Porter's Five Forces Analysis
    • 4.4.1. Bargaining Power of Buyers
    • 4.4.2. Bargaining Power of Suppliers
    • 4.4.3. Threat of New Entrants
    • 4.4.4. Intensity of Rivalry
    • 4.4.5. Threat of Substitutes
  • 4.5. Advantages of AutoML
  • 4.6. Value Chain Analysis

Chapter 5. Global Market Size and Forecast

  • 5.1. By Offering
    • 5.1.1. By Service
  • 5.2. By Deployment Type
  • 5.3. By Enterprise Size
  • 5.4. By Application
  • 5.5. By Industry
  • 5.6. By Region

Chapter 6. North America Market Size and Forecast

  • 6.1. By Offering
    • 6.1.1. By Service
  • 6.2. By Deployment Type
  • 6.3. By Enterprise Size
  • 6.4. By Application
  • 6.5. By Industry
  • 6.6. By Country

Chapter 7. Europe Market Size and Forecast

  • 7.1. By Offering
    • 7.1.1. By Service
  • 7.2. By Deployment Type
  • 7.3. By Enterprise Size
  • 7.4. By Application
  • 7.5. By Industry
  • 7.6. By Country

Chapter 8. APAC Market Size and Forecast

  • 8.1. By Offering
    • 8.1.1. By Service
  • 8.2. By Deployment Type
  • 8.3. By Enterprise Size
  • 8.4. By Application
  • 8.5. By Industry
  • 8.6. By Country

Chapter 9. LATAM Market Size and Forecast

  • 9.1. By Offering
    • 9.1.1. By Service
  • 9.2. By Deployment Type
  • 9.3. By Enterprise Size
  • 9.4. By Application
  • 9.5. By Industry
  • 9.6. By Country

Chapter 10. MEA Market Size and Forecast

  • 10.1. By Offering
    • 10.1.1. By Service
  • 10.2. By Deployment Type
  • 10.3. By Enterprise Size
  • 10.4. By Application
  • 10.5. By Industry
  • 10.6. By Country

Chapter 11. Competitive Landscape

  • 11.1. List of Key Players
  • 11.2. Market Presence Metric (Based on Popularity & Web Traffic)
  • 11.3. Recent Activities of Major Players
  • 11.4. Strategic Developments of Key Players
    • 11.4.1. Mergers and Acquisitions
    • 11.4.2. Partnerships
    • 11.4.3. Product/Service Launches
    • 11.4.4. Others

Chapter 12. Company Profiles

  • 12.1. DataRobot Inc.
    • 12.1.1. Business Overview
    • 12.1.2. Product and Service Offerings
  • 12.2. H2O.ai Inc.
    • 12.2.1. Business Overview
    • 12.2.2. Product and Service Offerings
  • 12.3. dotData Inc.
    • 12.3.1. Business Overview
    • 12.3.2. Product and Service Offerings
  • 12.4. EdgeVerve Systems Limited
    • 12.4.1. Business Overview
    • 12.4.2. Product and Service Offerings
  • 12.5. Amazon Web Services Inc.
    • 12.5.1. Business Overview
    • 12.5.2. Product and Service Offerings
  • 12.6. Squark
    • 12.6.1. Business Overview
    • 12.6.2. Product and Service Offerings
  • 12.7. Qlik Technologies Inc.
    • 12.7.1. Business Overview
    • 12.7.2. Product and Service Offerings
  • 12.8. SAS Institute Inc.
    • 12.8.1. Business Overview
    • 12.8.2. Product and Service Offerings
  • 12.9. Microsoft Corporation
    • 12.9.1. Business Overview
    • 12.9.2. Product and Service offerings
    • 12.9.3. Key Financial Summary
  • 12.1. Determined.ai Inc.
    • 12.10.1. Business Overview
    • 12.10.2. Product and Service Offerings
  • 12.11. JADBio - Gnosis DA S.A.
    • 12.11.1. Business Overview
    • 12.11.2. Product and Service Offerings
  • 12.12. BigML Inc.
    • 12.12.1. Business Overview
    • 12.12.2. Product and Service Offerings
  • 12.13. Splunk Inc.
    • 12.13.1. Business Overview
    • 12.13.2. Product and Service Offerings
    • 12.13.3. Key Financial Summary
  • 12.14. Tellius Inc.
    • 12.14.1. Business Overview
    • 12.14.2. Product and Service Offerings
  • 12.15. Aible Inc.
    • 12.15.1. Business Overview
    • 12.15.2. Product and Service Offerings
  • 12.16. International Business Machines (IBM) Corporation
    • 12.16.1. Business Overview
    • 12.16.2. Product and Service Offerings
    • 12.16.3. Key Financial Summary
  • 12.17. Google LLC
    • 12.17.1. Business Overview
    • 12.17.2. Product and Service Offerings
  • 12.18. RapidMiner
    • 12.18.1. Business Overview
    • 12.18.2. Product and Service Offerings
  • 12.19. TAZI AI
    • 12.19.1. Business Overview
    • 12.19.2. Product and Service Offerings
  • 12.2. MLJAR Sp. z o. o.
    • 12.20.1. Business Overview
    • 12.20.2. Product and Service Offerings
  • 12.21. Akkio Inc.
    • 12.21.1. Business Overview
    • 12.21.2. Product and Service Offerings
  • 12.22. Enhencer LLC
    • 12.22.1. Business Overview
    • 12.22.2. Product and Service Offerings
  • 12.23. Dataiku
    • 12.23.1. Business Overview
    • 12.23.2. Product and Service Offerings

Chapter 13. Appendix

  • 13.1. Sources and References
  • 13.2. Related Reports

LIST OF TABLES

  • TABLE 1: ANALYSIS PERIOD OF THE STUDY
  • TABLE 2: DRIVERS FOR THE MARKET: IMPACT ANALYSIS
  • TABLE 3: RESTRAINTS FOR THE MARKET: IMPACT ANALYSIS
  • TABLE 4: GLOBAL AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 5: GLOBAL AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 6: GLOBAL AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 7: GLOBAL AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 8: GLOBAL AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 9: GLOBAL AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 10: GLOBAL AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 11: GLOBAL AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 12: GLOBAL AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 13: GLOBAL AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 14: GLOBAL AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 15: GLOBAL AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 16: GLOBAL AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 17: GLOBAL AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 18: GLOBAL AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 19: GLOBAL AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 20: GLOBAL AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 21: GLOBAL AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 22: GLOBAL AUTOML MARKET, BY REGION, $M (2015-2022)
  • TABLE 23: GLOBAL AUTOML MARKET, BY REGION, $M (2023-2027)
  • TABLE 24: GLOBAL AUTOML MARKET, BY REGION, $M (2028-2030)
  • TABLE 25: NORTH AMERICA AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 26: NORTH AMERICA AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 27: NORTH AMERICA AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 28: NORTH AMERICA AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 29: NORTH AMERICA AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 30: NORTH AMERICA AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 31: NORTH AMERICA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 32: NORTH AMERICA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 33: NORTH AMERICA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 34: NORTH AMERICA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 35: NORTH AMERICA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 36: NORTH AMERICA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 37: NORTH AMERICA AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 38: NORTH AMERICA AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 39: NORTH AMERICA AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 40: NORTH AMERICA AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 41: NORTH AMERICA AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 42: NORTH AMERICA AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 43: NORTH AMERICA AUTOML MARKET, BY COUNTRY, $M (2015-2022)
  • TABLE 44: NORTH AMERICA AUTOML MARKET, BY COUNTRY, $M (2023-2027)
  • TABLE 45: NORTH AMERICA AUTOML MARKET, BY COUNTRY, $M (2028-2030)
  • TABLE 46: EUROPE AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 47: EUROPE AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 48: EUROPE AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 49: EUROPE AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 50: EUROPE AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 51: EUROPE AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 52: EUROPE AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 53: EUROPE AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 54: EUROPE AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 55: EUROPE AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 56: EUROPE AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 57: EUROPE AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 58: EUROPE AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 59: EUROPE AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 60: EUROPE AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 61: EUROPE AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 62: EUROPE AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 63: EUROPE AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 64: EUROPE AUTOML MARKET, BY COUNTRY, $M (2015-2022)
  • TABLE 65: EUROPE AUTOML MARKET, BY COUNTRY, $M (2023-2027)
  • TABLE 66: EUROPE AUTOML MARKET, BY COUNTRY, $M (2028-2030)
  • TABLE 67: APAC AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 68: APAC AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 69: APAC AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 70: APAC AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 71: APAC AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 72: APAC AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 73: APAC AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 74: APAC AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 75: APAC AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 76: APAC AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 77: APAC AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 78: APAC AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 79: APAC AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 80: APAC AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 81: APAC AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 82: APAC AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 83: APAC AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 84: APAC AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 85: APAC AUTOML MARKET, BY COUNTRY, $M (2015-2022)
  • TABLE 86: APAC AUTOML MARKET, BY COUNTRY, $M (2023-2027)
  • TABLE 87: APAC AUTOML MARKET, BY COUNTRY, $M (2028-2030)
  • TABLE 88: LATAM AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 89: LATAM AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 90: LATAM AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 91: LATAM AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 92: LATAM AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 93: LATAM AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 94: LATAM AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 95: LATAM AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 96: LATAM AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 97: LATAM AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 98: LATAM AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 99: LATAM AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 100: LATAM AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 101: LATAM AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 102: LATAM AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 103: LATAM AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 104: LATAM AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 105: LATAM AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 106: LATAM AUTOML MARKET, BY COUNTRY, $M (2015-2022)
  • TABLE 107: LATAM AUTOML MARKET, BY COUNTRY, $M (2023-2027)
  • TABLE 108: LATAM AUTOML MARKET, BY COUNTRY, $M (2028-2030)
  • TABLE 109: MEA AUTOML MARKET, BY OFFERING, $M (2015-2022)
  • TABLE 110: MEA AUTOML MARKET, BY OFFERING, $M (2023-2027)
  • TABLE 111: MEA AUTOML MARKET, BY OFFERING, $M (2028-2030)
  • TABLE 112: MEA AUTOML SERVICE MARKET, BY TYPE, $M (2015-2022)
  • TABLE 113: MEA AUTOML SERVICE MARKET, BY TYPE, $M (2023-2027)
  • TABLE 114: MEA AUTOML SERVICE MARKET, BY TYPE, $M (2028-2030)
  • TABLE 115: MEA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2022)
  • TABLE 116: MEA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2023-2027)
  • TABLE 117: MEA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2028-2030)
  • TABLE 118: MEA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2022)
  • TABLE 119: MEA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2023-2027)
  • TABLE 120: MEA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2028-2030)
  • TABLE 121: MEA AUTOML MARKET, BY APPLICATION, $M (2015-2022)
  • TABLE 122: MEA AUTOML MARKET, BY APPLICATION, $M (2023-2027)
  • TABLE 123: MEA AUTOML MARKET, BY APPLICATION, $M (2028-2030)
  • TABLE 124: MEA AUTOML MARKET, BY INDUSTRY, $M (2015-2022)
  • TABLE 125: MEA AUTOML MARKET, BY INDUSTRY, $M (2023-2027)
  • TABLE 126: MEA AUTOML MARKET, BY INDUSTRY, $M (2028-2030)
  • TABLE 127: MEA AUTOML MARKET, BY COUNTRY, $M (2015-2022)
  • TABLE 128: MEA AUTOML MARKET, BY COUNTRY, $M (2023-2027)
  • TABLE 129: MEA AUTOML MARKET, BY COUNTRY, $M (2028-2030)
  • TABLE 130: LIST OF KEY PLAYERS AND THEIR OFFERINGS
  • TABLE 131: DATAROBOT INC. - AT A GLANCE
  • TABLE 132: H2O.AI INC. - AT A GLANCE
  • TABLE 133: DOTDATA INC. - AT A GLANCE
  • TABLE 134: EDGEVERVE SYSTEMS LIMITED - AT A GLANCE
  • TABLE 135: AMAZON WEB SERVICES INC. - AT A GLANCE
  • TABLE 136: SQUARK - AT A GLANCE
  • TABLE 137: QLIK TECHNOLOGIES INC. - AT A GLANCE
  • TABLE 138: SAS INSTITUTE INC. - AT A GLANCE
  • TABLE 139: MICROSOFT CORPORATION - AT A GLANCE
  • TABLE 140: MICROSOFT CORPORATION - KEY FINANCIAL SUMMARY
  • TABLE 141: DETERMINED.AI INC. - AT A GLANCE
  • TABLE 142: JADBIO - GNOSIS DA S.A. - AT A GLANCE
  • TABLE 143: BIGML INC. - AT A GLANCE
  • TABLE 144: SPLUNK INC. - AT A GLANCE
  • TABLE 145: SPLUNK INC. - KEY FINANCIAL SUMMARY
  • TABLE 146: TELLIUS INC. - AT A GLANCE
  • TABLE 147: AIBLE INC. - AT A GLANCE
  • TABLE 148: IBM CORPORATION - AT A GLANCE
  • TABLE 149: IBM CORPORATION - KEY FINANCIAL SUMMARY
  • TABLE 150: GOOGLE LLC - AT A GLANCE
  • TABLE 151: RAPIDMINER - AT A GLANCE
  • TABLE 152: TAZI AI - AT A GLANCE
  • TABLE 153: MLJAR SP. Z O. O. - AT A GLANCE
  • TABLE 154: AKKIO INC. - AT A GLANCE
  • TABLE 155: ENHENCER LLC - AT A GLANCE
  • TABLE 156: DATAIKU - AT A GLANCE

LIST OF FIGURES

  • FIG. 1: RESEARCH SCOPE
  • FIG. 2: RESEARCH METHODOLOGY
  • FIG. 3: REGIONAL SPLIT OF PRIMARY AND SECONDARY RESEARCH
  • FIG. 4: BREAKDOWN OF PRIMARY RESEARCH BY REGION
  • FIG. 5: BREAKDOWN OF PRIMARY RESEARCH BY INDUSTRY PARTICIPANT
  • FIG. 6: BREAKDOWN OF PRIMARY RESEARCH BY COMPANY TYPE
  • FIG. 7: DATA TRIANGULATION APPROACH
  • FIG. 8: GLOBAL AUTOML MARKET SUMMARY
  • FIG. 9: BARGAINING POWER OF BUYERS
  • FIG. 10: BARGAINING POWER OF SUPPLIERS
  • FIG. 11: THREAT OF NEW ENTRANTS
  • FIG. 12: INTENSITY OF RIVALRY
  • FIG. 13: THREAT OF SUBSTITUTES
  • FIG. 14: VALUE CHAIN ANALYSIS
  • FIG. 15: GLOBAL AUTOML MARKET SNAPSHOT
  • FIG. 16: GLOBAL AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 17: GLOBAL AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 18: GLOBAL AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 19: GLOBAL AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 20: GLOBAL AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 21: GLOBAL AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 22: MAJOR WORLDWIDE MARKETS FOR AUTOML
  • FIG. 23: NORTH AMERICA AUTOML MARKET SNAPSHOT
  • FIG. 24: NORTH AMERICA AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 25: NORTH AMERICA AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 26: NORTH AMERICA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 27: NORTH AMERICA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 28: NORTH AMERICA AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 29: NORTH AMERICA AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 30: NORTH AMERICA AUTOML MARKET, BY COUNTRY, $M (2015-2030)
  • FIG. 31: EUROPE AUTOML MARKET SNAPSHOT
  • FIG. 32: EUROPE AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 33: EUROPE AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 34: EUROPE AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 35: EUROPE AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 36: EUROPE AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 37: EUROPE AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 38: EUROPE AUTOML MARKET, BY COUNTRY, $M (2015-2030)
  • FIG. 39: APAC AUTOML MARKET SNAPSHOT
  • FIG. 40: APAC AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 41: APAC AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 42: APAC AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 43: APAC AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 44: APAC AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 45: APAC AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 46: APAC AUTOML MARKET, BY COUNTRY, $M (2015-2030)
  • FIG. 47: LATAM AUTOML MARKET SNAPSHOT
  • FIG. 48: LATAM AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 49: LATAM AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 50: LATAM AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 51: LATAM AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 52: LATAM AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 53: LATAM AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 54: LATAM AUTOML MARKET, BY COUNTRY, $M (2015-2030)
  • FIG. 55: MEA AUTOML MARKET SNAPSHOT
  • FIG. 56: MEA AUTOML MARKET, BY OFFERING, $M (2015-2030)
  • FIG. 57: MEA AUTOML SERVICE MARKET, BY TYPE, $M (2015-2030)
  • FIG. 58: MEA AUTOML MARKET, BY DEPLOYMENT TYPE, $M (2015-2030)
  • FIG. 59: MEA AUTOML MARKET, BY ENTERPRISE SIZE, $M (2015-2030)
  • FIG. 60: MEA AUTOML MARKET, BY APPLICATION, $M (2015-2030)
  • FIG. 61: MEA AUTOML MARKET, BY INDUSTRY, $M (2015-2030)
  • FIG. 62: MEA AUTOML MARKET, BY COUNTRY, $M (2015-2030)
  • FIG. 63: MARKET PRESENCE METRIC (BASED ON POPULARITY & WEB TRAFFIC), 2021
  • FIG. 64: RECENT ACTIVITIES OF MAJOR PLAYERS
  • FIG. 65: REVENUE SPLIT BY GEOGRAPHY (2021)
  • FIG. 66: MICROSOFT CORPORATION - REVENUE SPLIT BY SEGMENT (2021)
  • FIG. 67: SPLUNK INC. - REVENUE SPLIT BY SEGMENT AND GEOGRAPHY (2022)
  • FIG. 68: IBM CORPORATION - REVENUE SPLIT BY SEGMENT AND GEOGRAPHY (2021)