合成データ生成市場：オファリング（ソリューション/プラットフォーム、サービス）、データタイプ（表形式、テキスト、画像、動画）、アプリケーション（AI/MLトレーニング＆開発、テストデータ管理）、垂直、地域別 - 2028年までの世界予測

Synthetic Data Generation Market by Offering (Solution/Platform and Services), Data Type (Tabular, Text, Image, and Video), Application (AI/ML Training & Development, Test Data Management), Vertical and Region - Global Forecast to 2028

世界の合成データ生成の規模は、2023年の3億米ドルから2028年には21億米ドルへと、予測期間中に45.7%の年間平均成長率（CAGR）で拡大すると予測されています。データプライバシーとGDPRやCCPAなどのコンプライア... もっと見る

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世界の合成データ生成の規模は、2023年の3億米ドルから2028年には21億米ドルへと、予測期間中に45.7%の年間平均成長率（CAGR）で拡大すると予測されています。データプライバシーとGDPRやCCPAなどのコンプライアンス規制の重要性が高まり、個人データを扱う組織のニーズが高まっています。AIへの投資の増加は、より洗練された新しい合成データ生成技術につながり、合成データ生成市場を牽引する。
データタイプ別では、テキストデータ・セグメントが予測期間中に最も高い成長率を記録する
データタイプ別では、テキストデータ分野が予測期間中に最も高い成長率を記録すると予想されています。人工知能（AI）および機械学習（ML）アプリケーションの需要の増加により、モデルの訓練と開発に大量のデータが必要となり、テキストデータ・セグメントをさらに牽引しています。
アプリケーションの中では、テストデータ管理分野が予測期間中に2番目に高い市場シェアを獲得しています。
アプリケーション分野では、テストデータ管理分野が予測期間中に2番目に高い市場シェアを獲得すると予想されます。テストや検証のために、高品質で多様な代表的データが必要であることが、この分野を牽引しています。企業は、合成データを用いてテストプロセスの有効性と効率性を高めることができ、製品品質の向上、市場投入までの時間の短縮、従来のテストデータ管理手法に関連するコストの削減が可能になります。
地域別では、アジア太平洋地域が予測期間中に最も高いCAGRで成長する"
アジアにおける合成データ生成市場は、急速なデジタル変革、データプライバシー規制の強化、AIやML技術の採用拡大、サイバーセキュリティへの懸念の高まり、スタートアップエコシステムの隆盛を背景に、大きな成長を遂げています。同地域の組織は、データ駆動型の課題への対応、規制への対応、AI・MLモデルの性能強化、サイバーセキュリティ対策の強化、イノベーションの推進を目的に、合成データ生成を活用しています。この地域がデジタル化に注力し、データ駆動型ソリューションへのニーズが高まっていることから、アジア太平洋地域の合成データ生成市場は、継続的な拡大と機会が見込まれています。
主な参加者のプロフィールの内訳は以下の通りです：
- 企業別ティア1：38％、ティア2：50％、ティア3：12
- 役職別役職別：Cレベルエグゼクティブ - 35%、ディレクター - 40%、その他* - 25
- 地域別北米：40％、欧州：20％、APAC：30％、中近東・アフリカ：5％、中南米：5
注）ティア1企業は売上高が100億米ドル以上、ティア2企業は売上高が全体の10～100億米ドル、ティア3企業は売上高が5億米ドル～10億米ドルです。
*その他、セールスマネジャー、マーケティングマネジャー、プロダクトマネジャーなど。 **Rest of World (RoW) はMEAとラテンアメリカを含みます。
出典業界専門家
この調査レポートは、合成データ生成市場における市場の可能性、ダイナミクス、主要ベンダーについて概説しています。合成データ生成の主要かつ革新的なベンダーには、Microsoft（米国）、Google（米国）、IBM（米国）、AWS（米国）、NVIDIA（米国）、OpenAI（米国）、Informatica（米国）、Broadcom（米国）、Sogeti（フランス）、Mphasis（インド）、Databricks（米国）、MOSTLY AI（オーストリア）、Tonic（米国）、MDClone（イスラエル）TCS（インド）、Hazy（英国）、Syntheia（英国）、Syntheized（英国）、Facteus（米国）、Anyverse（スペイン）、Neurolabs（スコットランド）、 Rendered.ai（米国）、Gretel（米国）、OneView（イスラエル）、GenRocket（米国）、YData（米国）、CVEDIA（英国）、Syntheticus（スイス）、AnyLogic（米国）、Bifrost AI（米国）、Anonos（米国）です。これらのベンダーは、合成データ生成市場における提供製品と市場シェアを拡大するために、新製品の発売、パートナーシップ、コラボレーションなど、多くの有機的および無機的な成長戦略を採用しています。
調査対象範囲
合成データ生成市場は、オファリング（ソリューション／プラットフォーム、サービス）、データタイプ（表形式、テキスト、画像、動画、その他）、アプリケーション（AI／MLトレーニング・開発、テストデータ管理、データ分析・可視化、企業データ共有、その他）、垂直（銀行・金融サービス・保険、ヘルスケア・生命科学、小売・EC、自動車・輸送、政府・防衛、IT・ITeS、製造、その他垂直）、地域によって区分されます。合成データ生成市場に関連する事業概要、サービス、主要戦略、新サービスおよび製品の発表、パートナーシップ、契約、コラボレーション、事業拡大、競争環境に関する洞察を提供するために、主要な業界プレイヤーの詳細な分析が実施されています。
本レポートを購入する理由
本レポートは、以下の点で市場リーダーや新規参入者に役立つと思われます：
- 合成データ生成市場を包括的にセグメント化し、異なる地域における市場全体とそのサブセグメントについて、最も近似した収益数を提供しています。
- 市場の脈動を理解し、主要な市場促進要因、阻害要因、課題、機会に関する情報を提供することで、ステークホルダーの理解を深めることができます。
- また、競合他社をより深く理解し、市場において自らのポジションを向上させるためのより多くの洞察を得ることができます。競争環境には、競合他社のエコシステム、新サービス開発、パートナーシップ、M&Aなどが含まれます。
本レポートは、以下のポイントに関する洞察を提供しています：

合成データ生成の成長に影響を与える主要な促進要因（AIと機械学習の導入、データプライバシーとコンプライアンスに対する需要の増加、コンテンツ作成の増加）、抑制要因（規制と倫理的配慮、質の高いデータとリアリズムの実現に関する問題）、機会（大規模言語モデルの展開の増加、人間のベースライン性能につながる生成MLの強固な改善）、課題（市場の成熟度の欠如、AIコストのかかる投資、熟練労働者の欠如）の解析。製品開発/イノベーション：合成データ生成における今後の技術、研究開発活動、新製品・サービス発表に関する詳細なインサイトを提供します。市場開発：有利な市場に関する包括的な情報 - 本レポートは、さまざまな地域の合成データ生成市場を分析しています。
市場の多様化：合成データ生成市場の新製品・サービス、未開拓の地域、最近の開発、投資に関する詳細な情報を提供します。競争力評価：Microsoft（米国）、Google（米国）、IBM（米国）、AWS（米国）、NVIDIA（米国）、OpenAI（米国）、Informatica（米国）、Broadcom（米国）などの主要企業の市場シェア、成長戦略、サービス提供について詳細に評価、Sogeti（フランス）、Mphasis（インド）、Databricks（米国）、MOSTLY AI（オーストリア）、Tonic（米国）、MDClone（イスラエル）TCS（インド）、Hazy（英国）、Syntheia（英国）、Syntheized（英国）、Facteus（米国）、Anyverse（スペイン）、Neurolabs（スコットランド）、 Rendered.ai（米国）、Gretel（米国）、OneView（イスラエル）、GenRocket（米国）、YData（米国）、CVEDIA（英国）、Syntheticus（スイス）、AnyLogic（米国）、Bifrost AI（米国）、Anonos（米国）。

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1 INTRODUCTION 40
1.1 STUDY OBJECTIVES 40
1.2 MARKET DEFINITION 40
1.2.1 INCLUSIONS & EXCLUSIONS 41
1.3 STUDY SCOPE 42
1.3.1 MARKET SEGMENTATION 42
1.3.2 REGIONS COVERED 43
1.4 YEARS CONSIDERED 43
1.5 CURRENCY CONSIDERED 44
TABLE 1 USD EXCHANGE RATE, 2019–2022 44
1.6 STAKEHOLDERS 44
2 RESEARCH METHODOLOGY 45
2.1 RESEARCH DATA 45
FIGURE 1 RESEARCH DESIGN 45
2.1.1 SECONDARY DATA 46
2.1.2 PRIMARY DATA 46
TABLE 2 KEY PARTICIPANTS OF PRIMARY INTERVIEWS 46
2.1.2.1 Breakup of primary profiles 47
2.1.2.2 Key industry insights 47
2.2 DATA TRIANGULATION 48
FIGURE 2 DATA TRIANGULATION 48
2.3 MARKET SIZE ESTIMATION 49
FIGURE 3 SYNTHETIC DATA GENERATION MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES 49
2.3.1 TOP-DOWN APPROACH 49
2.3.2 BOTTOM-UP APPROACH 50
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY, APPROACH 1 (SUPPLY-SIDE): REVENUE FROM SOLUTIONS/SERVICES OF SYNTHETIC DATA GENERATION MARKET 50
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY, APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF SYNTHETIC DATA GENERATION MARKET 51
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY, APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF SYNTHETIC DATA GENERATION MARKET 52
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF SYNTHETIC DATA GENERATION THROUGH OVERALL MARKET SPENDING 53
2.4 MARKET FORECAST 54
TABLE 3 FACTOR ANALYSIS 54
2.5 RESEARCH ASSUMPTIONS 55
2.6 LIMITATIONS AND RISK ASSESSMENT 56
2.7 IMPACT OF RECESSION ON SYNTHETIC DATA GENERATION MARKET 57
3 EXECUTIVE SUMMARY 58
FIGURE 8 ASIA PACIFIC TO ACHIEVE HIGHEST GROWTH DURING FORECAST PERIOD 59
4 PREMIUM INSIGHTS 60
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN SYNTHETIC DATA GENERATION MARKET 60
FIGURE 9 INCREASING INVESTMENTS IN AI TO DRIVE MARKET GROWTH 60
4.2 SYNTHETIC DATA GENERATION MARKET: BY KEY VERTICAL & REGION 60
FIGURE 10 BFSI SEGMENT AND NORTH AMERICA TO ACCOUNT FOR SIGNIFICANT SHARE IN 2023 60
FIGURE 11 SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER SHARE IN 2023 61
4.3 SYNTHETIC DATA GENERATION MARKET, BY REGION 61
FIGURE 12 NORTH AMERICA TO ACCOUNT FOR LARGEST SHARE IN 2023 61
5 MARKET OVERVIEW AND INDUSTRY TRENDS 62
5.1 INTRODUCTION 62
5.2 MARKET DYNAMICS 62
FIGURE 13 SYNTHETIC DATA GENERATION MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 62
5.2.1 DRIVERS 63
5.2.1.1 Rising adoption of AI and machine learning technologies 63
5.2.1.2 Increasing need for data privacy and compliance 63
5.2.1.3 Rise in investments in AI 63
5.2.1.4 Increase in content creation 64
FIGURE 14 SYNTHETIC DATA TO ACCOUNT FOR LARGER DATA VOLUME BY 2030 64
5.2.2 RESTRAINTS 64
5.2.2.1 Regulatory and ethical considerations 64
5.2.2.2 Issues related to achieving quality data and realism 64
5.2.3 OPPORTUNITIES 65
5.2.3.1 Increasing deployment of large language models 65
5.2.3.2 Growing interest of enterprises in commercializing synthetic images 65
5.2.3.3 Robust advancements in machine learning and computing innovation 65
5.2.4 CHALLENGES 66
5.2.4.1 Market immaturity 66
5.2.4.2 Lack of skilled workforce 66
5.2.4.3 High costs associated with high-end generative models 66
5.3 ETHICS AND IMPLICATIONS OF SYNTHETIC DATA GENERATION 67
5.3.1 PRIVACY PROTECTION 67
5.3.2 FAIRNESS 67
5.3.3 DATA OWNERSHIP AND CONSENT 67
5.3.4 UNINTENDED CONSEQUENCES 67
5.3.5 ACCOUNTABILITY AND TRANSPARENCY 67
5.3.6 FAIR REPRESENTATION 67
5.3.7 REGULATORY COMPLIANCE 67
5.4 ADVENT OF SYNTHETIC DATA GENERATION 68
5.5 HISTORY OF SYNTHETIC DATA GENERATION 69
FIGURE 15 HISTORY OF SYNTHETIC DATA GENERATION 69
5.6 TIMELINE OF ADVANCEMENTS IN SYNTHETIC DATA GENERATION MARKET 69
5.7 ECOSYSTEM ANALYSIS 71
FIGURE 16 ECOSYSTEM ANALYSIS 71
5.7.1 SYNTHETIC DATA GENERATION TECHNOLOGY PROVIDERS 71
5.7.2 SYNTHETIC DATA GENERATION CLOUD PLATFORM PROVIDERS 71
5.7.3 SYNTHETIC DATA GENERATION CLOUD END USERS 71
5.7.4 SYNTHETIC DATA GENERATION CLOUD REGULATORS 72
5.8 SYNTHETIC DATA GENERATION TECHNIQUES AND METHODS BASED ON DATA TYPES 72
5.8.1 TABULAR 72
5.8.1.1 Rule-based Methods 72
5.8.1.2 Data Augmentation 72
5.8.1.3 Generative Adversarial Networks (GANs) 73
5.8.1.4 Variational Autoencoders (VAEs) 73
5.8.1.5 Bayesian Networks 73
5.8.2 TEXT 73
5.8.2.1 Markov Chains 73
5.8.2.2 Neural Networks (RNNs) 73
5.8.2.3 Transformer Models 73
5.8.2.4 Language Models 73
5.8.2.5 Variational Autoencoders 73
5.8.3 IMAGES AND VIDEOS 74
5.8.3.1 Generative Adversarial Networks (GANs) 74
5.8.3.2 Variational Autoencoders (VAEs) 74
5.8.3.3 Conditional GANs 74
5.8.3.4 Image and Video Synthesis with Neural Networks 74
5.8.3.5 Style Transfer and Data Augmentation 74
5.8.4 TIME SERIES & TRANSACTIONAL DATA 74
5.8.4.1 Autoregressive Integrated Moving Average (ARIMA) 74
5.8.4.2 Long Short-Term Memory (LSTM) Networks 74
5.8.4.3 Hidden Markov Models (HMMs) 75
5.8.4.4 Sequence Generative Adversarial Networks (SeqGANs) 75
5.8.4.5 Gaussian Mixture Models (GMMs) 75
5.8.4.6 Synthetic Oversampling and Undersampling 75
5.9 CASE STUDY ANALYSIS 75
5.9.1 CASE STUDY 1: MOSTLY AI HELPED RETAIL BANK SHORTEN DEVELOPMENT OF SPRINTS BY SEVERAL DAYS 75
5.9.2 CASE STUDY 2: SWEDISH GOVERNMENT INCORPORATED ARTIFICIAL INTELLIGENCE INTO DAILY OPERATIONS 76
5.9.3 CASE STUDY 3: EVERLYWELL GAINED 5X DEPLOYMENT VELOCITY WITH SUPPORT FROM TONIC API 76
5.9.4 CASE STUDY 4: VODAFONE ADOPTED HAZY SYNTHETIC DATA TO QUICKLY AND ACCURATELY PREDICT CHURN 76
5.9.5 CASE STUDY 5: SCALE AI HELPED KALEIDO AI’S ML TEAM TO IMPROVE MODEL PERFORMANCE ON BUSINESS-CRITICAL EDGE CASES 77
5.10 SUPPLY CHAIN ANALYSIS 77
FIGURE 17 SUPPLY CHAIN ANALYSIS 77
5.11 REGULATORY LANDSCAPE 78
5.11.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 78
TABLE 4 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 78
TABLE 5 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 79
TABLE 6 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 79
TABLE 7 MIDDLE EAST & AFRICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 80
TABLE 8 LATIN AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 80
5.11.2 PAYMENT CARD INDUSTRY DATA SECURITY STANDARD 81
5.11.3 GRAMM-LEACH-BLILEY ACT 81
5.11.4 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT 81
5.11.5 GENERAL DATA PROTECTION REGULATION 82
5.11.6 PERSONAL INFORMATION PROTECTION AND ELECTRONIC DOCUMENTS ACT 82
5.11.7 INFORMATION SECURITY TECHNOLOGY: PERSONAL INFORMATION SECURITY SPECIFICATION GB/T 35273-2017 83
5.11.8 SECURE INDIA NATIONAL DIGITAL COMMUNICATIONS POLICY, 2018 83
5.11.9 GENERAL DATA PROTECTION LAW 83
5.11.10 LAW NO 13 OF 2016 ON PROTECTING PERSONAL DATA 84
5.11.11 NIST SPECIAL PUBLICATION 800-144, GUIDELINES ON SECURITY AND PRIVACY IN PUBLIC CLOUD COMPUTING 84
5.12 PATENT ANALYSIS 85
5.12.1 METHODOLOGY 85
5.12.2 PATENT APPLICATIONS 85
FIGURE 18 NUMBER OF PATENTS GRANTED ANNUALLY, 2019–2022 85
5.12.3 TOP 15 PATENT APPLICANTS IN LAST 10 YEARS 86
FIGURE 19 TOP 15 PATENT APPLICANTS IN LAST 10 YEARS 86
5.12.4 TOP 15 PATENT OWNERS IN LAST 10 YEARS 86
FIGURE 20 TOP 15 PATENT OWNERS IN LAST 10 YEARS 86
5.13 KEY CONFERENCES & EVENTS 87
TABLE 9 KEY CONFERENCES & EVENTS, 2023–2024 87
5.14 PRICING ANALYSIS 89
TABLE 10 AVERAGE SELLING PRICE ANALYSIS 89
5.15 PORTER’S FIVE FORCES ANALYSIS 90
TABLE 11 IMPACT OF PORTER’S FORCES ON SYNTHETIC DATA GENERATION MARKET 90
5.15.1 THREAT FROM NEW ENTRANTS 90
5.15.2 THREAT FROM SUBSTITUTES 90
5.15.3 BARGAINING POWER OF SUPPLIERS 91
5.15.4 BARGAINING POWER OF BUYERS 91
5.15.5 INTENSITY OF COMPETITIVE RIVALRY 91
5.16 KEY STAKEHOLDERS AND BUYING CRITERIA 91
5.16.1 KEY STAKEHOLDERS IN BUYING PROCESS 91
FIGURE 21 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 91
TABLE 12 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 92
5.16.2 BUYING CRITERIA 92
FIGURE 22 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 92
TABLE 13 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 92
5.17 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS OF SYNTHETIC DATA GENERATION MARKET 93
FIGURE 23 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS 93
5.17.1 BUSINESS MODELS IN SYNTHETIC DATA GENERATION MARKET 93
5.17.1.1 Software licensing 93
5.17.1.2 Data-as-a-Service (DaaS) 93
5.17.1.3 Custom development 93
5.17.1.4 Consulting and professional services 93
5.17.1.5 Partnerships and collaborations 94
5.17.1.6 Data monetization 94
5.17.1.7 Integration with existing platforms 94
5.17.1.8 Research and development 94
5.17.1.9 Freemium model 94
5.17.1.10 Open source 94
6 SYNTHETIC DATA GENERATION MARKET, BY OFFERING 95
6.1 INTRODUCTION 96
6.1.1 OFFERINGS: SYNTHETIC DATA GENERATION MARKET DRIVERS 96
FIGURE 24 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD 96
TABLE 14 SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 97
TABLE 15 SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 97
6.2 SOLUTIONS 97
TABLE 16 SOLUTIONS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 97
TABLE 17 SOLUTIONS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 98
6.3 SERVICES 98
FIGURE 25 MANAGED SERVICES SEGMENT TO REGISTER HIGHER GROWTH DURING FORECAST PERIOD 98
TABLE 18 SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 99
TABLE 19 SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 99
TABLE 20 SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2019–2022 (USD MILLION) 99
TABLE 21 SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2023–2028 (USD MILLION) 99
6.3.1 PROFESSIONAL SERVICES 100
6.3.1.1 Rising demand for specialized expertise in synthetic data generation to boost market growth 100
FIGURE 26 SYSTEM INTEGRATION AND IMPLEMENTATION SEGMENT TO ACHIEVE HIGHEST GROWTH DURING FORECAST PERIOD 100
TABLE 22 SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 100
TABLE 23 SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 101
TABLE 24 PROFESSIONAL SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 101
TABLE 25 PROFESSIONAL SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 101
6.3.1.1.1 Training and consulting 101
TABLE 26 TRAINING AND CONSULTING: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 102
TABLE 27 TRAINING AND CONSULTING: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 102
6.3.1.1.2 System integration and implementation 102
TABLE 28 SYSTEM INTEGRATION AND IMPLEMENTATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 103
TABLE 29 SYSTEM INTEGRATION AND IMPLEMENTATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 103
6.3.1.1.3 Support and maintenance 103
TABLE 30 SUPPORT AND MAINTENANCE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 104
TABLE 31 SUPPORT AND MAINTENANCE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 104
6.3.2 MANAGED SERVICES 104
6.3.2.1 Need for end-to-end management of synthetic data generation to drive market for managed services 104
TABLE 32 MANAGED SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 105
TABLE 33 MANAGED SERVICES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 105
7 SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE 106
7.1 INTRODUCTION 107
7.1.1 DATA TYPES: SYNTHETIC DATA GENERATION MARKET DRIVERS 107
FIGURE 27 TEXT SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD 107
TABLE 34 SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2019–2022 (USD MILLION) 107
TABLE 35 SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2023–2028 (USD MILLION) 108
7.2 TABULAR 108
7.2.1 DEMAND FOR PRIVACY PRESERVATION TO DRIVE GENERATION OF TABULAR DATA 108
TABLE 36 TABULAR: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 108
TABLE 37 TABULAR: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 109
7.3 TEXT 109
7.3.1 NEED TO CREATE LABELED TRAINING DATASETS FOR NATURAL LANGUAGE PROCESSING TASKS TO DRIVE MARKET GROWTH 109
TABLE 38 TEXT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 109
TABLE 39 TEXT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 110
7.4 IMAGES AND VIDEOS 110
7.4.1 DEMAND FOR COMPUTER VISION TRAINING, IMAGE RECOGNITION, AND VIDEO ANALYSIS MODELS TO DRIVE MARKET GROWTH 110
TABLE 40 IMAGES AND VIDEOS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 110
TABLE 41 IMAGES AND VIDEOS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 111
7.5 OTHER DATA TYPES 111
TABLE 42 OTHER DATA TYPES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 111
TABLE 43 OTHER DATA TYPES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 112
8 SYNTHETIC DATA GENERATION MARKET, BY APPLICATION 113
8.1 INTRODUCTION 114
8.1.1 APPLICATIONS: SYNTHETIC DATA GENERATION MARKET DRIVERS 114
FIGURE 28 AI/ML TRAINING AND DEVELOPMENT SEGMENT TO ACCOUNT FOR LARGEST SHARE IN 2023 114
TABLE 44 SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 115
TABLE 45 SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 115
8.2 AI/ML TRAINING AND DEVELOPMENT 115
8.2.1 NEED FOR SCALABLE AND DIVERSE DATASETS FOR TRAINING MODELS TO DRIVE ADOPTION OF SYNTHETIC DATA GENERATION 115
TABLE 46 AI/ML TRAINING AND DEVELOPMENT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 116
TABLE 47 AI/ML TRAINING AND DEVELOPMENT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 116
8.3 TEST DATA MANAGEMENT 116
8.3.1 NEED TO ENHANCE EFFICIENCY OF SOFTWARE TESTING APPLICATIONS TO PROPEL SYNTHETIC DATA GENERATION MARKET 116
TABLE 48 TEST DATA MANAGEMENT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 117
TABLE 49 TEST DATA MANAGEMENT: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 117
8.4 DATA ANALYTICS AND VISUALIZATION 117
8.4.1 GROWING NEED TO SAFEGUARD DATA PRIVACY TO BOOST SYNTHETIC DATA GENERATION FOR DATA ANALYTICS AND VISUALIZATION 117
TABLE 50 DATA ANALYTICS AND VISUALIZATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 118
TABLE 51 DATA ANALYTICS AND VISUALIZATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 118
8.5 ENTERPRISE DATA SHARING 118
8.5.1 NEED TO LEVERAGE POWER OF SHARED DATA TO ENCOURAGE PLAYERS TO ADOPT ENTERPRISE DATA SHARING AND DETECTION 118
TABLE 52 ENTERPRISE DATA SHARING AND RETENTION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 119
TABLE 53 ENTERPRISE DATA SHARING AND RETENTION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 119
8.6 OTHER APPLICATIONS 119
TABLE 54 OTHER APPLICATIONS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 120
TABLE 55 OTHER APPLICATIONS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 120
9 SYNTHETIC DATA GENERATION MARKET, BY VERTICAL 121
9.1 INTRODUCTION 122
9.1.1 VERTICALS: SYNTHETIC DATA GENERATION MARKET DRIVERS 122
FIGURE 29 HEALTHCARE AND LIFE SCIENCES SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 123
TABLE 56 SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 123
TABLE 57 SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 124
9.2 BANKING, FINANCIAL SERVICES, AND INSURANCE (BFSI) 124
9.2.1 NEED FOR REGULATED LANDSCAPE WITH STRINGENT DATA PRIVACY REQUIREMENTS TO DRIVE MARKET GROWTH 124
9.2.2 BFSI: SYNTHETIC DATA GENERATION MARKET USE CASES 124
TABLE 58 BFSI: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 125
TABLE 59 BFSI: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 125
9.3 HEALTHCARE AND LIFE SCIENCES 125
9.3.1 DEMAND FOR PRIVACY IN HEALTHCARE SECTOR TO BOOST ADOPTION OF SYNTHETIC DATA GENERATION 125
9.3.2 HEALTHCARE AND LIFE SCIENCES: SYNTHETIC DATA GENERATION MARKET USE CASES 126
TABLE 60 HEALTHCARE AND LIFE SCIENCES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 126
TABLE 61 HEALTHCARE AND LIFE SCIENCES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 127
9.4 RETAIL AND E-COMMERCE 127
9.4.1 SYNTHETIC DATA GENERATION TO ENABLE RETAIL AND E-COMMERCE COMPANIES TO CREATE REPRESENTATIVE DATASETS 127
9.4.2 RETAIL AND E-COMMERCE: SYNTHETIC DATA GENERATION MARKET USE CASES 127
TABLE 62 RETAIL AND E-COMMERCE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 128
TABLE 63 RETAIL AND E-COMMERCE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 128
9.5 AUTOMOTIVE AND TRANSPORTATION 129
9.5.1 DEMAND FOR OPTIMIZED VEHICLE PERFORMANCE TO PROPEL ADOPTION OF SYNTHETIC DATA GENERATION 129
9.5.2 AUTOMOTIVE AND TRANSPORTATION: SYNTHETIC DATA GENERATION MARKET USE CASES 129
TABLE 64 AUTOMOTIVE AND TRANSPORTATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 130
TABLE 65 AUTOMOTIVE AND TRANSPORTATION: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 130
9.6 GOVERNMENT AND DEFENSE 130
9.6.1 RISING NEED TO PROTECT SENSITIVE INFORMATION TO DRIVE USE OF SYNTHETIC DATA GENERATION IN GOVERNMENT AND DEFENSE SEGMENT 130
9.6.2 GOVERNMENT AND DEFENSE: SYNTHETIC DATA GENERATION MARKET USE CASES 131
TABLE 66 GOVERNMENT AND DEFENSE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 131
TABLE 67 GOVERNMENT AND DEFENSE: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 132
9.7 IT AND ITES 132
9.7.1 NEED FOR DATA PRIVACY AND SECURITY IN IT AND ITES SECTOR TO ENABLE PLAYERS TO UNDERSTAND VALUE OF SYNTHETIC DATA GENERATION 132
9.7.2 IT AND ITES: SYNTHETIC DATA GENERATION MARKET USE CASES 132
TABLE 68 IT AND ITES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 133
TABLE 69 IT AND ITES: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 133
9.8 MANUFACTURING 134
9.8.1 GROWING NEED TO IMPROVE PRODUCT DESIGN AND OPTIMIZATION TO PROPEL SYNTHETIC DATA GENERATION MARKET GROWTH 134
9.8.2 MANUFACTURING: SYNTHETIC DATA GENERATION MARKET USE CASES 134
TABLE 70 MANUFACTURING: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 135
TABLE 71 MANUFACTURING: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 135
9.9 OTHER VERTICALS 135
TABLE 72 OTHER VERTICALS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 136
TABLE 73 OTHER VERTICALS: SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 136
10 SYNTHETIC DATA GENERATION MARKET, BY REGION 137
10.1 INTRODUCTION 138
FIGURE 30 ASIA PACIFIC TO REGISTER HIGHEST GROWTH DURING FORECAST PERIOD 138
TABLE 74 SYNTHETIC DATA GENERATION MARKET, BY REGION, 2019–2022 (USD MILLION) 138
TABLE 75 SYNTHETIC DATA GENERATION MARKET, BY REGION, 2023–2028 (USD MILLION) 139
10.2 NORTH AMERICA 139
10.2.1 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET DRIVERS 139
10.2.2 NORTH AMERICA: RECESSION IMPACT 140
FIGURE 31 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET SNAPSHOT 140
TABLE 76 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 141
TABLE 77 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 141
TABLE 78 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2019–2022 (USD MILLION) 141
TABLE 79 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2023–2028 (USD MILLION) 141
TABLE 80 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2019–2022 (USD MILLION) 142
TABLE 81 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2023–2028 (USD MILLION) 142
TABLE 82 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 142
TABLE 83 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 142
TABLE 84 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 143
TABLE 85 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 143
TABLE 86 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 143
TABLE 87 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 144
TABLE 88 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 144
TABLE 89 NORTH AMERICA: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 144
10.2.3 US 145
10.2.3.1 Technological advancements and widespread application of synthetic data generation to drive market 145
TABLE 90 US: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 145
TABLE 91 US: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 145
10.2.4 CANADA 146
10.2.4.1 Need to enhance productivity and improve customer satisfaction to drive market growth 146
TABLE 92 CANADA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 146
TABLE 93 CANADA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 146
10.3 EUROPE 146
10.3.1 EUROPE: SYNTHETIC DATA GENERATION MARKET DRIVERS 147
10.3.2 EUROPE: RECESSION IMPACT 147
TABLE 94 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 148
TABLE 95 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 148
TABLE 96 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2019–2022 (USD MILLION) 148
TABLE 97 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2023–2028 (USD MILLION) 148
TABLE 98 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2019–2022 (USD MILLION) 149
TABLE 99 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2023–2028 (USD MILLION) 149
TABLE 100 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 149
TABLE 101 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 149
TABLE 102 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 150
TABLE 103 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 150
TABLE 104 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 150
TABLE 105 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 151
TABLE 106 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 151
TABLE 107 EUROPE: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 152
10.3.3 UK 152
10.3.3.1 Government initiatives to drive demand for synthetic data generation 152
TABLE 108 UK: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 152
TABLE 109 UK: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 152
10.3.4 GERMANY 153
10.3.4.1 Surge in adoption of artificial intelligence to drive demand for synthetic data generation tools in research and development 153
TABLE 110 GERMANY: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 153
TABLE 111 GERMANY: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 153
10.3.5 FRANCE 154
10.3.5.1 Growing demand for research and educational excellence to drive demand for AI-enabled technologies 154
TABLE 112 FRANCE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 154
TABLE 113 FRANCE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 154
10.3.6 ITALY 155
10.3.6.1 Demand for deep learning model to perform source separation and music generation to drive market growth 155
TABLE 114 ITALY: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 155
TABLE 115 ITALY: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 155
10.3.7 SPAIN 156
10.3.7.1 Need to develop AI solutions and language models to drive market for synthetic data generation 156
TABLE 116 SPAIN: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 156
TABLE 117 SPAIN: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 156
10.3.8 FINLAND 156
10.3.8.1 Growing demand for AI applications in education sector to drive market growth 156
10.3.9 REST OF EUROPE 157
TABLE 118 REST OF EUROPE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 157
TABLE 119 REST OF EUROPE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 157
10.4 ASIA PACIFIC 158
10.4.1 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET DRIVERS 158
10.4.2 ASIA PACIFIC: RECESSION IMPACT 158
FIGURE 32 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET SNAPSHOT 159
TABLE 120 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 159
TABLE 121 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 160
TABLE 122 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2019–2022 (USD MILLION) 160
TABLE 123 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2023–2028 (USD MILLION) 160
TABLE 124 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2019–2022 (USD MILLION) 160
TABLE 125 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2023–2028 (USD MILLION) 161
TABLE 126 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 161
TABLE 127 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 161
TABLE 128 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 161
TABLE 129 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 162
TABLE 130 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 162
TABLE 131 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 162
TABLE 132 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 163
TABLE 133 ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 163
10.4.3 CHINA 163
10.4.3.1 Growth in technology sector to boost popularity of synthetic data generation solutions 163
TABLE 134 CHINA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 164
TABLE 135 CHINA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 164
10.4.4 INDIA 164
10.4.4.1 Rise in digital transformation across industry verticals to drive market growth 164
TABLE 136 INDIA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 164
TABLE 137 INDIA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 165
10.4.5 JAPAN 165
10.4.5.1 Need to digitalize pharma industry to drive adoption of synthetic data generation solutions 165
TABLE 138 JAPAN: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 165
TABLE 139 JAPAN: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 166
10.4.6 SOUTH KOREA 166
10.4.6.1 Rise in initiatives by government to boost adoption of synthetic data generation tools 166
TABLE 140 SOUTH KOREA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 166
TABLE 141 SOUTH KOREA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 166
10.4.7 SINGAPORE 167
10.4.7.1 Steady progress made in AI advancements to drive market for synthetic data generation solutions 167
TABLE 142 SINGAPORE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 167
TABLE 143 SINGAPORE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 167
10.4.8 AUSTRALIA & NEW ZEALAND 167
10.4.8.1 Popularity of ChatGPT and large language models to propel popularity of synthetic data generation solutions 167
TABLE 144 AUSTRALIA & NEW ZEALAND: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 168
TABLE 145 AUSTRALIA & NEW ZEALAND: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 168
10.4.9 REST OF ASIA PACIFIC 168
TABLE 146 REST OF ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 169
TABLE 147 REST OF ASIA PACIFIC: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 169
10.5 MIDDLE EAST & AFRICA 169
10.5.1 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET DRIVERS 169
10.5.2 MIDDLE EAST & AFRICA: RECESSION IMPACT 170
TABLE 148 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 170
TABLE 149 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 170
TABLE 150 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2019–2022 (USD MILLION) 170
TABLE 151 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY DATA TYPE, 2023–2028 (USD MILLION) 171
TABLE 152 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2019–2022 (USD MILLION) 171
TABLE 153 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY SERVICE, 2023–2028 (USD MILLION) 171
TABLE 154 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 171
TABLE 155 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 172
TABLE 156 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 172
TABLE 157 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 172
TABLE 158 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 173
TABLE 159 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 173
TABLE 160 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 174
TABLE 161 MIDDLE EAST & AFRICA: SYNTHETIC DATA GENERATION MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 174
10.5.3 SAUDI ARABIA 174
10.5.3.1 Major investments by tech giants to drive demand for synthetic data generation solutions 174
TABLE 162 SAUDI ARABIA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 175
TABLE 163 SAUDI ARABIA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 175
10.5.4 UAE 175
10.5.4.1 Adoption of trailblazing technologies for advanced education system to boost market growth 175
TABLE 164 UAE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 176
TABLE 165 UAE: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 176
10.5.5 SOUTH AFRICA 176
10.5.5.1 Demand for advancements in healthcare sector to drive market for synthetic data generation solutions 176
TABLE 166 SOUTH AFRICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 176
TABLE 167 SOUTH AFRICA: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 177
10.5.6 ISRAEL 177
10.5.6.1 Strong cluster of synthetic data generation and AI startups to lead to market growth 177
TABLE 168 ISRAEL: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2019–2022 (USD MILLION) 177
TABLE 169 ISRAEL: SYNTHETIC DATA GENERATION MARKET, BY OFFERING, 2023–2028 (USD MILLION) 177
10.5.7 REST OF MIDDLE EAST & AFRICA 178

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Table of Contents

Summary

The global synthetic data generation size is expected to grow from USD 0.3 billion in 2023 to USD 2.1 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 45.7% during the forecast period. The rising importance of data privacy and compliance regulations, such as GDPR and CCPA, drive organizations' need to handle personal data. Increasing investments in AI lead to new and more sophisticated synthetic data generation techniques driving the synthetic data generation market.
By data type, text data to segment to record a highest growth rate during the forecast period
By data type, the text data segment is expected to have the highest growth rate during the forecast period. The increasing demand for artificial intelligence (AI) and machine learning (ML) applications requires large amounts of data to train and develop models, further driving the text data segment.
Among applications, Test data management segment has the second-highest market share during the forecast period.
Under the applications segment, the Test data management segment is expected to have second the highest market share during the forecast period. The need for high-quality, diverse, and representative data for testing and validation purposes will drive the segment. Businesses can enhance the effectiveness and efficiency of their testing processes using synthetic data leading to improved product quality, faster time-to-market, and reduced costs associated with traditional test data management approaches.
Among regions, Asia Pacific to grow at the highest CAGR during the forecast period"
The synthetic data generation market in Asia is experiencing significant growth driven by rapid digital transformation, increasing data privacy regulations, growing adoption of AI and ML technologies, rising cybersecurity concerns, and a thriving startup ecosystem. Organizations in the region are leveraging synthetic data generation to address data-driven challenges, comply with regulations, enhance AI and ML model performance, strengthen cybersecurity measures, and drive innovation. With the region's focus on digitalization and the emerging need for data-driven solutions, Asia Pacific's synthetic data generation market is poised for continued expansion and opportunities.
The breakup of the profiles of the primary participants is given below:
• By Company: Tier 1 – 38%, Tier 2 – 50%, and Tier 3 – 12%
• By Designation: C-Level Executives – 35%, Directors– 40%, Others*–25%
• By Region: North America – 40%, Europe – 20%, APAC – 30%, and Middle East and Africa-5%, Latin America-5%
Note: Tier 1 companies have revenues over USD 10 billion; tier 2 companies' revenue ranges between USD 1 and 10 billion of the overall revenues; and tier 3 companies' revenue ranges between USD 500 million and USD 1 billion.
*Others include sales managers, marketing managers, and product managers. **Rest of World (RoW) includes MEA and Latin America.
Source: Industry Experts
This research study outlines the market potential, dynamics, and major vendors operating in the synthetic data generation market. Key and innovative vendors in synthetic data generation include Microsoft (US), Google (US), IBM (US), AWS (US), NVIDIA (US), OpenAI (US), Informatica (US), Broadcom (US), Sogeti (France), Mphasis (India), Databricks (US), MOSTLY AI (Austria), Tonic (US), MDClone (Israel) TCS (India), Hazy (UK), Synthesia (UK), Synthesized (UK), Facteus (US), Anyverse (Spain), Neurolabs (Scotland), Rendered.ai (US), Gretel (US), OneView (Israel), GenRocket (US), YData (US), CVEDIA (UK), Syntheticus (Switzerland), AnyLogic (US), Bifrost AI (US), Anonos (US). These vendors have adopted many organic and inorganic growth strategies, such as new product launches, partnerships, and collaborations, to expand their offerings and market shares in the synthetic data generation market.
Research Coverage
The synthetic data generation market is segmented into Offering (Solution/Platform and Services), Data Type (Tabular, Text, Image, and Video, Others), Application (AI/ML Training and Development, Test Data Management, Data analytics & visualization, Enterprise Data Sharing, Others), Vertical (Banking, Financial Services, and Insurance, Healthcare & Life sciences, Retail & E-commerce, Automotive & Transportation, Government & Defense, IT and ITeS, Manufacturing, Other Verticals) and Region. A detailed analysis of the key industry players has been undertaken to provide insights into their business overviews; services; key strategies; new service and product launches; partnerships, agreements, collaborations; business expansions; and competitive landscape associated with the synthetic data generation market.
Reasons to Buy the Report
The report would help the market leaders and new entrants in the following ways:
• It comprehensively segments the synthetic data generation market and provides the closest approximations of the revenue numbers for the overall market and its subsegments across different regions.
• It would help stakeholders understand the pulse of the market and provide information on the key market drivers, restraints, challenges, and opportunities.
• It would help stakeholders understand their competitors better and gain more insights to enhance their positions in the market. The competitive landscape includes a competitor ecosystem, new service developments, partnerships, and mergers and acquisitions.
The report provides insights on the following pointers:

Analysis of key drivers (AI and Machine Learning adoption, increasing demand for data privacy and compliance, the rise in content creation), restraints (regulatory and ethical considerations, issues related to achieving quality data and realism), opportunities (increasing deployment of large language models, robust improvement in generative ML leading to human baseline performance), and challenges (lack of maturity in the market, AI costly investments, lack of skilled workforce) influencing the growth of the synthetic data generation. Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in synthetic data generation. Market Development: Comprehensive information about lucrative markets – the report analyses the synthetic data generation market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the synthetic data generation market. Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players like Microsoft (US), Google (US), IBM (US), AWS (US), NVIDIA (US), OpenAI (US), Informatica (US), Broadcom (US), Sogeti (France), Mphasis (India), Databricks (US), MOSTLY AI (Austria), Tonic (US), MDClone (Israel) TCS (India), Hazy (UK), Synthesia (UK), Synthesized (UK), Facteus (US), Anyverse (Spain), Neurolabs (Scotland), Rendered.ai (US), Gretel (US), OneView (Israel), GenRocket (US), YData (US), CVEDIA (UK), Syntheticus (Switzerland), AnyLogic (US), Bifrost AI (US), Anonos (US).

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ご注文は、お電話またはWEBから承ります。お見積もりの作成もお気軽にご相談ください。

本レポートと同分野（通信・IT）の最新刊レポート

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