表紙:自動機械学習の市場規模とシェア分析:提供形態別、展開タイプ別、企業規模別、用途別、業界別 - 世界の産業需要予測(2030年まで)
市場調査レポート
商品コード
1222230

自動機械学習の市場規模とシェア分析:提供形態別、展開タイプ別、企業規模別、用途別、業界別 - 世界の産業需要予測(2030年まで)

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: | 発行: Prescient & Strategic Intelligence | ページ情報: 英文 221 Pages | 納期: 2~3営業日

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=152.41円
自動機械学習の市場規模とシェア分析:提供形態別、展開タイプ別、企業規模別、用途別、業界別 - 世界の産業需要予測(2030年まで)
出版日: 2023年01月01日
発行: Prescient & Strategic Intelligence
ページ情報: 英文 221 Pages
納期: 2~3営業日
  • 全表示
  • 概要
  • 図表
  • 目次
概要

世界の自動機械学習の市場規模は、2022年の6億3,100万米ドルから、2030年までに154億9,930万米ドルに達し、2022年から2030年にかけてCAGRで49.2%の成長が予測されています。市場の発展の主な要因には、効果的な不正発見ソリューションに対する需要の高まりや、パーソナライズされた製品推奨に対するニーズの高まりが挙げられます。

当レポートでは、世界の自動機械学習市場について調査分析し、市場力学、セグメント別・地域別の市場分析、競合情勢、主要企業プロファイルなどの情報を提供しています。

目次

第1章 調査の背景

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 イントロダクション

  • 市場セグメントの定義
    • 提供形態別
      • プラットホーム
      • サービス
    • 展開タイプ別
      • オンプレミス
      • クラウド
    • 企業規模別
      • 大企業
      • 中小企業
    • 用途別
      • 不正検出
      • 販売・マーケティング管理
      • 医療検査
      • 輸送の最適化
      • その他
    • 業界別
      • BFSI
      • IT ・通信
      • ヘルスケア
      • 政府
      • 小売
      • 製造業
      • その他
  • 市場力学
    • 動向
      • クラウドベースプラットフォームへの選好の高まり
    • 促進要因
      • 効率的な不正検出ソリューションに対する需要の増加
      • パーソナライズされた製品推奨に対するニーズの高まり
      • 予測リードスコアリングの重要性の高まり
      • 市場予測に対する促進要因の影響分析
    • 抑制要因
      • 技術的な熟練人材の不足
      • 市場予測に対する抑制要因の影響分析
    • 機会
      • 成長するヘルスケア産業
      • 効果的な品揃えの重要性の高まり
  • 自動機械学習市場に対するCOVID-19の影響
  • ポーターのファイブフォース分析
  • 自動機械学習の利点
  • バリューチェーン分析

第5章 世界市場規模と予測

  • 提供形態別
    • サービス別
  • 展開タイプ別
  • 企業規模別
  • 用途別
  • 業界別
  • 地域別

第6章 北米の市場規模と予測

第7章 欧州の市場規模と予測

第8章 アジア太平洋の市場規模と予測

第9章 ラテンアメリカの市場規模と予測

第10章 中東・アフリカの市場規模と予測

第11章 競合情勢

  • 主要企業のリスト
  • 市場プレゼンス指標(人気度・ウェブトラフィックに基づく)
  • 主要企業の最近の活動
  • 主要企業の戦略的展開
    • 合併・買収
    • パートナーシップ
    • 製品/サービスの発売
    • その他

第12章 企業プロファイル

  • 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 付録

図表

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)
目次
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