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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 - Forecast to 2028

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    Report

  • 261 Pages
  • June 2023
  • Region: Global
  • Markets and Markets
  • ID: 5821206
Description Jump to:

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.

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).

Table of Contents

1 Introduction
1.1 Study Objectives
1.2 Market Definition
1.2.1 Inclusions & Exclusions
1.3 Study Scope
1.3.1 Market Segmentation
1.3.2 Regions Covered
1.4 Years Considered
1.5 Currency Considered
Table 1 USD Exchange Rate, 2019-2022
1.6 Stakeholders

2 Research Methodology
2.1 Research Data
Figure 1 Research Design
2.1.1 Secondary Data
2.1.2 Primary Data
Table 2 Key Participants of Primary Interviews
2.1.2.1 Breakup of Primary Profiles
2.1.2.2 Key Industry Insights
2.2 Data Triangulation
Figure 2 Data Triangulation
2.3 Market Size Estimation
Figure 3 Synthetic Data Generation Market: Top-Down and Bottom-Up Approaches
2.3.1 Top-Down Approach
2.3.2 Bottom-Up Approach
Figure 4 Market Size Estimation Methodology, Approach 1 (Supply-Side): Revenue from Solutions/Services of Market
Figure 5 Market Size Estimation Methodology, Approach 2, Bottom-Up (Supply-Side): Collective Revenue from All Solutions/Services of Market
Figure 6 Market Size Estimation Methodology, Approach 3, Bottom-Up (Supply-Side): Collective Revenue from All Solutions/Services of Market
Figure 7 Market Size Estimation Methodology - Approach 4, Bottom-Up (Demand-Side): Share of Synthetic Data Generation Through Overall Market Spending
2.4 Market Forecast
Table 3 Factor Analysis
2.5 Research Assumptions
2.6 Limitations and Risk Assessment
2.7 Impact of Recession on Synthetic Data Generation Market

3 Executive Summary
Figure 8 Asia-Pacific to Achieve Highest Growth During Forecast Period

4 Premium Insights
4.1 Attractive Opportunities for Players in Synthetic Data Generation Market
Figure 9 Increasing Investments in Ai to Drive Market Growth
4.2 Market: by Key Vertical & Region
Figure 10 Bfsi Segment and North America to Account for Significant Share in 2023
Figure 11 Solutions Segment to Account for Larger Share in 2023
4.3 Market, by Region
Figure 12 North America to Account for Largest Share in 2023

5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
Figure 13 Synthetic Data Generation Market: Drivers, Restraints, Opportunities, and Challenges
5.2.1 Drivers
5.2.1.1 Rising Adoption of Ai and Machine Learning Technologies
5.2.1.2 Increasing Need for Data Privacy and Compliance
5.2.1.3 Rise in Investments in Ai
5.2.1.4 Increase in Content Creation
Figure 14 Synthetic Data to Account for Larger Data Volume by 2030
5.2.2 Restraints
5.2.2.1 Regulatory and Ethical Considerations
5.2.2.2 Issues Related to Achieving Quality Data and Realism
5.2.3 Opportunities
5.2.3.1 Increasing Deployment of Large Language Models
5.2.3.2 Growing Interest of Enterprises in Commercializing Synthetic Images
5.2.3.3 Robust Advancements in Machine Learning and Computing Innovation
5.2.4 Challenges
5.2.4.1 Market Immaturity
5.2.4.2 Lack of Skilled Workforce
5.2.4.3 High Costs Associated with High-End Generative Models
5.3 Ethics and Implications of Synthetic Data Generation
5.3.1 Privacy Protection
5.3.2 Fairness
5.3.3 Data Ownership and Consent
5.3.4 Unintended Consequences
5.3.5 Accountability and Transparency
5.3.6 Fair Representation
5.3.7 Regulatory Compliance
5.4 Advent of Synthetic Data Generation
5.5 History of Synthetic Data Generation
Figure 15 History of Synthetic Data Generation
5.6 Timeline of Advancements in Synthetic Data Generation Market
5.7 Ecosystem Analysis
Figure 16 Ecosystem Analysis
5.7.1 Synthetic Data Generation Technology Providers
5.7.2 Synthetic Data Generation Cloud Platform Providers
5.7.3 Synthetic Data Generation Cloud End-users
5.7.4 Synthetic Data Generation Cloud Regulators
5.8 Synthetic Data Generation Techniques and Methods Based on Data Types
5.8.1 Tabular
5.8.1.1 Rule-Based Methods
5.8.1.2 Data Augmentation
5.8.1.3 Generative Adversarial Networks (Gans)
5.8.1.4 Variational Autoencoders (Vaes)
5.8.1.5 Bayesian Networks
5.8.2 Text
5.8.2.1 Markov Chains
5.8.2.2 Neural Networks (Rnns)
5.8.2.3 Transformer Models
5.8.2.4 Language Models
5.8.2.5 Variational Autoencoders
5.8.3 Images and Videos
5.8.3.1 Generative Adversarial Networks (Gans)
5.8.3.2 Variational Autoencoders (Vaes)
5.8.3.3 Conditional Gans
5.8.3.4 Image and Video Synthesis with Neural Networks
5.8.3.5 Style Transfer and Data Augmentation
5.8.4 Time Series & Transactional Data
5.8.4.1 Autoregressive Integrated Moving Average (Arima)
5.8.4.2 Long Short-Term Memory (Lstm) Networks
5.8.4.3 Hidden Markov Models (Hmms)
5.8.4.4 Sequence Generative Adversarial Networks (Seqgans)
5.8.4.5 Gaussian Mixture Models (Gmms)
5.8.4.6 Synthetic Oversampling and Undersampling
5.9 Case Study Analysis
5.9.1 Case Study 1: Mostly Ai Helped Retail Bank Shorten Development of Sprints by Several Days
5.9.2 Case Study 2: Swedish Government Incorporated Artificial Intelligence into Daily Operations
5.9.3 Case Study 3: Everlywell Gained 5X Deployment Velocity with Support from Tonic Api
5.9.4 Case Study 4: Vodafone Adopted Hazy Synthetic Data to Quickly and Accurately Predict Churn
5.9.5 Case Study 5: Scale Ai Helped Kaleido Ai's Ml Team to Improve Model Performance on Business-Critical Edge Cases
5.10 Supply Chain Analysis
Figure 17 Supply Chain Analysis
5.11 Regulatory Landscape
5.11.1 Regulatory Bodies, Government Agencies, and Other Organizations
Table 4 North America: Regulatory Bodies, Government Agencies, and Other Organizations
Table 5 Europe: Regulatory Bodies, Government Agencies, and Other Organizations
Table 6 Asia-Pacific: Regulatory Bodies, Government Agencies, and Other Organizations
Table 7 Middle East & Africa: Regulatory Bodies, Government Agencies, and Other Organizations
Table 8 Latin America: Regulatory Bodies, Government Agencies, and Other Organizations
5.11.2 Payment Card Industry Data Security Standard
5.11.3 Gramm-Leach-Bliley Act
5.11.4 Health Insurance Portability and Accountability Act
5.11.5 General Data Protection Regulation
5.11.6 Personal Information Protection and Electronic Documents Act
5.11.7 Information Security Technology: Personal Information Security Specification Gb/T 35273-2017
5.11.8 Secure India National Digital Communications Policy, 2018
5.11.9 General Data Protection Law
5.11.10 Law No 13 of 2016 on Protecting Personal Data
5.11.11 Nist Special Publication 800-144, Guidelines on Security and Privacy in Public Cloud Computing
5.12 Patent Analysis
5.12.1 Methodology
5.12.2 Patent Applications
Figure 18 Number of Patents Granted Annually, 2019-2022
5.12.3 Top 15 Patent Applicants in Last 10 Years
Figure 19 Top 15 Patent Applicants in Last 10 Years
5.12.4 Top 15 Patent Owners in Last 10 Years
Figure 20 Top 15 Patent Owners in Last 10 Years
5.13 Key Conferences & Events
Table 9 Key Conferences & Events, 2023-2024
5.14 Pricing Analysis
Table 10 Average Selling Price Analysis
5.15 Porter's Five Forces Analysis
Table 11 Impact of Porter's Forces on Synthetic Data Generation Market
5.15.1 Threat from New Entrants
5.15.2 Threat from Substitutes
5.15.3 Bargaining Power of Suppliers
5.15.4 Bargaining Power of Buyers
5.15.5 Intensity of Competitive Rivalry
5.16 Key Stakeholders and Buying Criteria
5.16.1 Key Stakeholders in Buying Process
Figure 21 Influence of Stakeholders on Buying Process for Top Three Applications
Table 12 Influence of Stakeholders on Buying Process for Top Three Applications
5.16.2 Buying Criteria
Figure 22 Key Buying Criteria for Top Three Applications
Table 13 Key Buying Criteria for Top Three Applications
5.17 Trends/Disruptions Impacting Buyers/Clients of Synthetic Data Generation Market
Figure 23 Trends/Disruptions Impacting Buyers/Clients
5.17.1 Business Models in Market
5.17.1.1 Software Licensing
5.17.1.2 Data-As-A-Service (Daas)
5.17.1.3 Custom Development
5.17.1.4 Consulting and Professional Services
5.17.1.5 Partnerships and Collaborations
5.17.1.6 Data Monetization
5.17.1.7 Integration with Existing Platforms
5.17.1.8 Research and Development
5.17.1.9 Freemium Model
5.17.1.10 Open Source

6 Synthetic Data Generation Market, by Offering
6.1 Introduction
6.1.1 Offerings: Market Drivers
Figure 24 Services Segment to Register Higher CAGR During Forecast Period
Table 14 Market, by Offering, 2019-2022 (USD Million)
Table 15 Market, by Offering, 2023-2028 (USD Million)
6.2 Solutions
Table 16 Solutions: Market, by Region, 2019-2022 (USD Million)
Table 17 Solutions: Market, by Region, 2023-2028 (USD Million)
6.3 Services
Figure 25 Managed Services Segment to Register Higher Growth During Forecast Period
Table 18 Services: Market, by Region, 2019-2022 (USD Million)
Table 19 Services: Market, by Region, 2023-2028 (USD Million)
Table 20 Market, by Service, 2019-2022 (USD Million)
Table 21 Market, by Service, 2023-2028 (USD Million)
6.3.1 Professional Services
6.3.1.1 Rising Demand for Specialized Expertise in Synthetic Data Generation to Boost Market Growth
Figure 26 System Integration and Implementation Segment to Achieve Highest Growth During Forecast Period
Table 22 Synthetic Data Generation Market, by Professional Service, 2019-2022 (USD Million)
Table 23 Market, by Professional Service, 2023-2028 (USD Million)
Table 24 Professional Services: Market, by Region, 2019-2022 (USD Million)
Table 25 Professional Services: Market, by Region, 2023-2028 (USD Million)
6.3.1.1.1 Training and Consulting
Table 26 Training and Consulting: Market, by Region, 2019-2022 (USD Million)
Table 27 Training and Consulting: Market, by Region, 2023-2028 (USD Million)
6.3.1.1.2 System Integration and Implementation
Table 28 System Integration and Implementation: Market, by Region, 2019-2022 (USD Million)
Table 29 System Integration and Implementation: Market, by Region, 2023-2028 (USD Million)
6.3.1.1.3 Support and Maintenance
Table 30 Support and Maintenance: Market, by Region, 2019-2022 (USD Million)
Table 31 Support and Maintenance: Market, by Region, 2023-2028 (USD Million)
6.3.2 Managed Services
6.3.2.1 Need for End-To-End Management of Synthetic Data Generation to Drive Market for Managed Services
Table 32 Managed Services: Market, by Region, 2019-2022 (USD Million)
Table 33 Managed Services: Market, by Region, 2023-2028 (USD Million)

7 Synthetic Data Generation Market, by Data Type
7.1 Introduction
7.1.1 Data Types: Market Drivers
Figure 27 Text Segment to Register Highest CAGR During Forecast Period
Table 34 Market, by Data Type, 2019-2022 (USD Million)
Table 35 Market, by Data Type, 2023-2028 (USD Million)
7.2 Tabular
7.2.1 Demand for Privacy Preservation to Drive Generation of Tabular Data
Table 36 Tabular: Market, by Region, 2019-2022 (USD Million)
Table 37 Tabular: Market, by Region, 2023-2028 (USD Million)
7.3 Text
7.3.1 Need to Create Labeled Training Datasets for Natural Language Processing Tasks to Drive Market Growth
Table 38 Text: Market, by Region, 2019-2022 (USD Million)
Table 39 Text: Market, by Region, 2023-2028 (USD Million)
7.4 Images and Videos
7.4.1 Demand for Computer Vision Training, Image Recognition, and Video Analysis Models to Drive Market Growth
Table 40 Images and Videos: Market, by Region, 2019-2022 (USD Million)
Table 41 Images and Videos: Market, by Region, 2023-2028 (USD Million)
7.5 Other Data Types
Table 42 Other Data Types: Market, by Region, 2019-2022 (USD Million)
Table 43 Other Data Types: Market, by Region, 2023-2028 (USD Million)

8 Synthetic Data Generation Market, by Application
8.1 Introduction
8.1.1 Applications: Market Drivers
Figure 28 Ai/Ml Training and Development Segment to Account for Largest Share in 2023
Table 44 Market, by Application, 2019-2022 (USD Million)
Table 45 Market, by Application, 2023-2028 (USD Million)
8.2 Ai/Ml Training and Development
8.2.1 Need for Scalable and Diverse Datasets for Training Models to Drive Adoption of Synthetic Data Generation
Table 46 Ai/Ml Training and Development: Market, by Region, 2019-2022 (USD Million)
Table 47 Ai/Ml Training and Development: Market, by Region, 2023-2028 (USD Million)
8.3 Test Data Management
8.3.1 Need to Enhance Efficiency of Software Testing Applications to Propel Market
Table 48 Test Data Management: Synthetic Data Generation Market, by Region, 2019-2022 (USD Million)
Table 49 Test Data Management: Market, by Region, 2023-2028 (USD Million)
8.4 Data Analytics and Visualization
8.4.1 Growing Need to Safeguard Data Privacy to Boost Synthetic Data Generation for Data Analytics and Visualization
Table 50 Data Analytics and Visualization: Market, by Region, 2019-2022 (USD Million)
Table 51 Data Analytics and Visualization: Market, by Region, 2023-2028 (USD Million)
8.5 Enterprise Data Sharing
8.5.1 Need to Leverage Power of Shared Data to Encourage Players to Adopt Enterprise Data Sharing and Detection
Table 52 Enterprise Data Sharing and Retention: Market, by Region, 2019-2022 (USD Million)
Table 53 Enterprise Data Sharing and Retention: Market, by Region, 2023-2028 (USD Million)
8.6 Other Applications
Table 54 Other Applications: Market, by Region, 2019-2022 (USD Million)
Table 55 Other Applications: Market, by Region, 2023-2028 (USD Million)

9 Synthetic Data Generation Market, by Vertical
9.1 Introduction
9.1.1 Verticals: Market Drivers
Figure 29 Healthcare and Life Sciences Segment to Grow at Highest CAGR During Forecast Period
Table 56 Market, by Vertical, 2019-2022 (USD Million)
Table 57 Market, by Vertical, 2023-2028 (USD Million)
9.2 Banking, Financial Services, and Insurance (Bfsi)
9.2.1 Need for Regulated Landscape with Stringent Data Privacy Requirements to Drive Market Growth
9.2.2 Bfsi: Market Use Cases
Table 58 Bfsi: Market, by Region, 2019-2022 (USD Million)
Table 59 Bfsi: Market, by Region, 2023-2028 (USD Million)
9.3 Healthcare and Life Sciences
9.3.1 Demand for Privacy in Healthcare Sector to Boost Adoption of Synthetic Data Generation
9.3.2 Healthcare and Life Sciences: Market Use Cases
Table 60 Healthcare and Life Sciences: Market, by Region, 2019-2022 (USD Million)
Table 61 Healthcare and Life Sciences: Synthetic Data Generation Market, by Region, 2023-2028 (USD Million)
9.4 Retail and E-Commerce
9.4.1 Synthetic Data Generation to Enable Retail and E-Commerce Companies to Create Representative Datasets
9.4.2 Retail and E-Commerce: Market Use Cases
Table 62 Retail and E-Commerce: Market, by Region, 2019-2022 (USD Million)
Table 63 Retail and E-Commerce: Market, by Region, 2023-2028 (USD Million)
9.5 Automotive and Transportation
9.5.1 Demand for Optimized Vehicle Performance to Propel Adoption of Synthetic Data Generation
9.5.2 Automotive and Transportation: Market Use Cases
Table 64 Automotive and Transportation: Market, by Region, 2019-2022 (USD Million)
Table 65 Automotive and Transportation: Market, by Region, 2023-2028 (USD Million)
9.6 Government and Defense
9.6.1 Rising Need to Protect Sensitive Information to Drive Use of Synthetic Data Generation in Government and Defense Segment
9.6.2 Government and Defense: Synthetic Data Generation Market Use Cases
Table 66 Government and Defense: Market, by Region, 2019-2022 (USD Million)
Table 67 Government and Defense: Market, by Region, 2023-2028 (USD Million)
9.7 It and Ites
9.7.1 Need for Data Privacy and Security in It and Ites Sector to Enable Players to Understand Value of Synthetic Data Generation
9.7.2 It and Ites: Market Use Cases
Table 68 It and Ites: Market, by Region, 2019-2022 (USD Million)
Table 69 It and Ites: Market, by Region, 2023-2028 (USD Million)
9.8 Manufacturing
9.8.1 Growing Need to Improve Product Design and Optimization to Propel Market Growth
9.8.2 Manufacturing: Market Use Cases
Table 70 Manufacturing: Market, by Region, 2019-2022 (USD Million)
Table 71 Manufacturing: Market, by Region, 2023-2028 (USD Million)
9.9 Other Verticals
Table 72 Other Verticals: Market, by Region, 2019-2022 (USD Million)
Table 73 Other Verticals: Market, by Region, 2023-2028 (USD Million)

10 Synthetic Data Generation Market, by Region
10.1 Introduction
Figure 30 Asia-Pacific to Register Highest Growth During Forecast Period
Table 74 Market, by Region, 2019-2022 (USD Million)
Table 75 Market, by Region, 2023-2028 (USD Million)
10.2 North America
10.2.1 North America: Market Drivers
10.2.2 North America: Recession Impact
Figure 31 North America: Market Snapshot
Table 76 North America: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 77 North America: Market, by Offering, 2023-2028 (USD Million)
Table 78 North America: Market, by Data Type, 2019-2022 (USD Million)
Table 79 North America: Market, by Data Type, 2023-2028 (USD Million)
Table 80 North America: Market, by Service, 2019-2022 (USD Million)
Table 81 North America: Market, by Service, 2023-2028 (USD Million)
Table 82 North America: Market, by Professional Service, 2019-2022 (USD Million)
Table 83 North America: Market, by Professional Service, 2023-2028 (USD Million)
Table 84 North America: Market, by Application, 2019-2022 (USD Million)
Table 85 North America: Market, by Application, 2023-2028 (USD Million)
Table 86 North America: Market, by Vertical, 2019-2022 (USD Million)
Table 87 North America: Market, by Vertical, 2023-2028 (USD Million)
Table 88 North America: Market, by Country, 2019-2022 (USD Million)
Table 89 North America: Market, by Country, 2023-2028 (USD Million)
10.2.3 US
10.2.3.1 Technological Advancements and Widespread Application of Synthetic Data Generation to Drive Market
Table 90 US: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 91 US: Market, by Offering, 2023-2028 (USD Million)
10.2.4 Canada
10.2.4.1 Need to Enhance Productivity and Improve Customer Satisfaction to Drive Market Growth
Table 92 Canada: Market, by Offering, 2019-2022 (USD Million)
Table 93 Canada: Market, by Offering, 2023-2028 (USD Million)
10.3 Europe
10.3.1 Europe: Market Drivers
10.3.2 Europe: Recession Impact
Table 94 Europe: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 95 Europe: Market, by Offering, 2023-2028 (USD Million)
Table 96 Europe: Market, by Data Type, 2019-2022 (USD Million)
Table 97 Europe: Market, by Data Type, 2023-2028 (USD Million)
Table 98 Europe: Market, by Service, 2019-2022 (USD Million)
Table 99 Europe: Market, by Service, 2023-2028 (USD Million)
Table 100 Europe: Market, by Professional Service, 2019-2022 (USD Million)
Table 101 Europe: Market, by Professional Service, 2023-2028 (USD Million)
Table 102 Europe: Market, by Application, 2019-2022 (USD Million)
Table 103 Europe: Market, by Application, 2023-2028 (USD Million)
Table 104 Europe: Market, by Vertical, 2019-2022 (USD Million)
Table 105 Europe: Market, by Vertical, 2023-2028 (USD Million)
Table 106 Europe: Market, by Country, 2019-2022 (USD Million)
Table 107 Europe: Market, by Country, 2023-2028 (USD Million)
10.3.3 UK
10.3.3.1 Government Initiatives to Drive Demand for Synthetic Data Generation
Table 108 UK: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 109 UK: Market, by Offering, 2023-2028 (USD Million)
10.3.4 Germany
10.3.4.1 Surge in Adoption of Artificial Intelligence to Drive Demand for Synthetic Data Generation Tools in Research and Development
Table 110 Germany: Market, by Offering, 2019-2022 (USD Million)
Table 111 Germany: Market, by Offering, 2023-2028 (USD Million)
10.3.5 France
10.3.5.1 Growing Demand for Research and Educational Excellence to Drive Demand for Ai-Enabled Technologies
Table 112 France: Market, by Offering, 2019-2022 (USD Million)
Table 113 France: Market, by Offering, 2023-2028 (USD Million)
10.3.6 Italy
10.3.6.1 Demand for Deep Learning Model to Perform Source Separation and Music Generation to Drive Market Growth
Table 114 Italy: Market, by Offering, 2019-2022 (USD Million)
Table 115 Italy: Market, by Offering, 2023-2028 (USD Million)
10.3.7 Spain
10.3.7.1 Need to Develop Ai Solutions and Language Models to Drive Market for Synthetic Data Generation
Table 116 Spain: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 117 Spain: Market, by Offering, 2023-2028 (USD Million)
10.3.8 Finland
10.3.8.1 Growing Demand for Ai Applications in Education Sector to Drive Market Growth
10.3.9 Rest of Europe
Table 118 Rest of Europe: Market, by Offering, 2019-2022 (USD Million)
Table 119 Rest of Europe: Market, by Offering, 2023-2028 (USD Million)
10.4 Asia-Pacific
10.4.1 Asia-Pacific: Market Drivers
10.4.2 Asia-Pacific: Recession Impact
Figure 32 Asia-Pacific: Synthetic Data Generation Market Snapshot
Table 120 Asia-Pacific: Market, by Offering, 2019-2022 (USD Million)
Table 121 Asia-Pacific: Market, by Offering, 2023-2028 (USD Million)
Table 122 Asia-Pacific: Market, by Data Type, 2019-2022 (USD Million)
Table 123 Asia-Pacific: Market, by Data Type, 2023-2028 (USD Million)
Table 124 Asia-Pacific: Market, by Service, 2019-2022 (USD Million)
Table 125 Asia-Pacific: Market, by Service, 2023-2028 (USD Million)
Table 126 Asia-Pacific: Market, by Professional Service, 2019-2022 (USD Million)
Table 127 Asia-Pacific: Market, by Professional Service, 2023-2028 (USD Million)
Table 128 Asia-Pacific: Market, by Application, 2019-2022 (USD Million)
Table 129 Asia-Pacific: Market, by Application, 2023-2028 (USD Million)
Table 130 Asia-Pacific: Market, by Vertical, 2019-2022 (USD Million)
Table 131 Asia-Pacific: Market, by Vertical, 2023-2028 (USD Million)
Table 132 Asia-Pacific: Market, by Country, 2019-2022 (USD Million)
Table 133 Asia-Pacific: Market, by Country, 2023-2028 (USD Million)
10.4.3 China
10.4.3.1 Growth in Technology Sector to Boost Popularity of Synthetic Data Generation Solutions
Table 134 China: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 135 China: Market, by Offering, 2023-2028 (USD Million)
10.4.4 India
10.4.4.1 Rise in Digital Transformation Across Industry Verticals to Drive Market Growth
Table 136 India: Market, by Offering, 2019-2022 (USD Million)
Table 137 India: Market, by Offering, 2023-2028 (USD Million)
10.4.5 Japan
10.4.5.1 Need to Digitalize Pharma Industry to Drive Adoption of Synthetic Data Generation Solutions
Table 138 Japan: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 139 Japan: Market, by Offering, 2023-2028 (USD Million)
10.4.6 South Korea
10.4.6.1 Rise in Initiatives by Government to Boost Adoption of Synthetic Data Generation Tools
Table 140 South Korea: Market, by Offering, 2019-2022 (USD Million)
Table 141 South Korea: Market, by Offering, 2023-2028 (USD Million)
10.4.7 Singapore
10.4.7.1 Steady Progress Made in Ai Advancements to Drive Market for Synthetic Data Generation Solutions
Table 142 Singapore: Market, by Offering, 2019-2022 (USD Million)
Table 143 Singapore: Market, by Offering, 2023-2028 (USD Million)
10.4.8 Australia & New Zealand
10.4.8.1 Popularity of Chatgpt and Large Language Models to Propel Popularity of Synthetic Data Generation Solutions
Table 144 Australia & New Zealand: Market, by Offering, 2019-2022 (USD Million)
Table 145 Australia & New Zealand: Market, by Offering, 2023-2028 (USD Million)
10.4.9 Rest of Asia-Pacific
Table 146 Rest of Asia-Pacific: Market, by Offering, 2019-2022 (USD Million)
Table 147 Rest of Asia-Pacific: Market, by Offering, 2023-2028 (USD Million)
10.5 Middle East & Africa
10.5.1 Middle East & Africa: Market Drivers
10.5.2 Middle East & Africa: Recession Impact
Table 148 Middle East & Africa: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 149 Middle East & Africa: Market, by Offering, 2023-2028 (USD Million)
Table 150 Middle East & Africa: Market, by Data Type, 2019-2022 (USD Million)
Table 151 Middle East & Africa: Market, by Data Type, 2023-2028 (USD Million)
Table 152 Middle East & Africa: Market, by Service, 2019-2022 (USD Million)
Table 153 Middle East & Africa: Market, by Service, 2023-2028 (USD Million)
Table 154 Middle East & Africa: Market, by Professional Service, 2019-2022 (USD Million)
Table 155 Middle East & Africa: Market, by Professional Service, 2023-2028 (USD Million)
Table 156 Middle East & Africa: Market, by Application, 2019-2022 (USD Million)
Table 157 Middle East & Africa: Market, by Application, 2023-2028 (USD Million)
Table 158 Middle East & Africa: Market, by Vertical, 2019-2022 (USD Million)
Table 159 Middle East & Africa: Market, by Vertical, 2023-2028 (USD Million)
Table 160 Middle East & Africa: Market, by Country, 2019-2022 (USD Million)
Table 161 Middle East & Africa: Market, by Country, 2023-2028 (USD Million)
10.5.3 Saudi Arabia
10.5.3.1 Major Investments by Tech Giants to Drive Demand for Synthetic Data Generation Solutions
Table 162 Saudi Arabia: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 163 Saudi Arabia: Market, by Offering, 2023-2028 (USD Million)
10.5.4 UAE
10.5.4.1 Adoption of Trailblazing Technologies for Advanced Education System to Boost Market Growth
Table 164 UAE: Market, by Offering, 2019-2022 (USD Million)
Table 165 UAE: Market, by Offering, 2023-2028 (USD Million)
10.5.5 South Africa
10.5.5.1 Demand for Advancements in Healthcare Sector to Drive Market for Synthetic Data Generation Solutions
Table 166 South Africa: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 167 South Africa: Market, by Offering, 2023-2028 (USD Million)
10.5.6 Israel
10.5.6.1 Strong Cluster of Synthetic Data Generation and Ai Startups to Lead to Market Growth
Table 168 Israel: Market, by Offering, 2019-2022 (USD Million)
Table 169 Israel: Market, by Offering, 2023-2028 (USD Million)
10.5.7 Rest of Middle East & Africa
10.6 Latin America
10.6.1 Latin America: Market Drivers
10.6.2 Latin America: Recession Impact
Table 170 Latin America: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 171 Latin America: Market, by Offering, 2023-2028 (USD Million)
Table 172 Latin America: Market, by Data Type, 2019-2022 (USD Million)
Table 173 Latin America: Market, by Data Type, 2023-2028 (USD Million)
Table 174 Latin America: Market, by Service, 2019-2022 (USD Million)
Table 175 Latin America: Market, by Service, 2023-2028 (USD Million)
Table 176 Latin America: Market, by Professional Service, 2019-2022 (USD Million)
Table 177 Latin America: Market, by Professional Service, 2023-2028 (USD Million)
Table 178 Latin America: Market, by Application, 2019-2022 (USD Million)
Table 179 Latin America: Market, by Application, 2023-2028 (USD Million)
Table 180 Latin America: Market, by Vertical, 2019-2022 (USD Million)
Table 181 Latin America: Market, by Vertical, 2023-2028 (USD Million)
Table 182 Latin America: Market, by Country, 2019-2022 (USD Million)
Table 183 Latin America: Market, by Country, 2023-2028 (USD Million)
10.6.3 Brazil
10.6.3.1 Establishment of Cloud Region to Propel Market Growth of Synthetic Data Generation Solutions
Table 184 Brazil: Synthetic Data Generation Market, by Offering, 2019-2022 (USD Million)
Table 185 Brazil: Market, by Offering, 2023-2028 (USD Million)
10.6.4 Mexico
10.6.4.1 Demand for Digitalizing Banking Sector to Boost Adoption of Market
Table 186 Mexico: Market, by Offering, 2019-2022 (USD Million)
Table 187 Mexico: Market, by Offering, 2023-2028 (USD Million)
10.6.5 Argentina
10.6.5.1 Use of Synthetic Data Generation Solutions by Government to Address Economic and Political Instability to Drive Market Growth
10.6.6 Rest of Latin America
Table 188 Rest of Latin America: Market, by Offering, 2019-2022 (USD Million)
Table 189 Rest of Latin America: Market, by Offering, 2023-2028 (USD Million)

11 Competitive Landscape
11.1 Overview
11.2 Strategies Adopted by Key Players
Table 190 Strategies Adopted by Key Players
11.3 Revenue Analysis
11.3.1 Historical Revenue Analysis for Key Players
Figure 33 Historical Revenue Analysis for Key Players, 2020-2022 (USD Million)
11.4 Market Share Analysis
Figure 34 Market Share Analysis for Key Players, 2022
Table 191 Market: Intensity of Competitive Rivalry
11.5 Evaluation Quadrant Matrix for Key Players
11.5.1 Stars
11.5.2 Emerging Leaders
11.5.3 Pervasive Players
11.5.4 Participants
Figure 35 Evaluation Quadrant Matrix for Key Players, 2022
11.6 Competitive Benchmarking for Key Players
Table 192 Product Footprint Analysis for Key Players, 2022
11.7 Evaluation Quadrant Matrix for Startups/Smes
11.7.1 Progressive Companies
11.7.2 Responsive Companies
11.7.3 Dynamic Companies
11.7.4 Starting Blocks
Figure 36 Evaluation Quadrant Matrix for Startups/Smes, 2022
11.8 Competitive Benchmarking for Startups/Smes
Table 193 Market: Detailed List of Key Startups/Smes
Table 194 Product Footprint Analysis for Startups/Smes, 2022
11.9 Competitive Scenario
11.9.1 Product Launches and Enhancements
Table 195 Product Launches and Enhancements, 2020-2023
11.9.2 Deals
Table 196 Deals, 2020-2023

12 Company Profiles
(Business Overview, Products Offered, Recent Developments, Analyst's View Right to Win, Strategic Choices Made, Weaknesses and Competitive Threats) *
12.1 Introduction
12.2 Key Players
12.2.1 Microsoft
Table 197 Microsoft: Business Overview
Figure 37 Microsoft: Company Snapshot
Table 198 Microsoft: Solutions/Services Offered
Table 199 Microsoft: Product Launches and Enhancements
Table 200 Microsoft: Deals
12.2.2 Google
Table 201 Google: Business Overview
Figure 38 Google: Company Snapshot
Table 202 Google: Solutions/Services Offered
Table 203 Google: Deals
12.2.3 Ibm
Table 204 Ibm: Business Overview
Figure 39 Ibm: Company Snapshot
Table 205 Ibm: Solutions/Services Offered
Table 206 Ibm: Product Launches and Enhancements
Table 207 Ibm: Deals
12.2.4 Aws
Table 208 Aws: Business Overview
Figure 40 Aws: Company Snapshot
Table 209 Aws: Solutions/Services Offered
Table 210 Aws: Product Launches and Enhancements
Table 211 Aws: Deals
12.2.5 Nvidia Corporation
Table 212 Nvidia Corporation: Business Overview
Figure 41 Nvidia Corporation: Company Snapshot
Table 213 Nvidia Corporation: Solutions/Services Offered
12.2.6 Openai
Table 214 Openai: Business Overview
Table 215 Openai: Solutions/Services Offered
Table 216 Openai: Product Launches and Enhancements
Table 217 Openai: Deals
12.2.7 Informatica
Table 218 Informatica: Business Overview
Figure 42 Informatica: Company Snapshot
Table 219 Informatica: Solutions/Services Offered
Table 220 Informatica: Product Launches and Enhancements
Table 221 Informatica: Deals
12.2.8 Broadcom
Table 222 Broadcom: Business Overview
Figure 43 Broadcom: Company Snapshot
Table 223 Broadcom: Solutions/Services Offered
12.2.9 Capgemini
Table 224 Capgemini: Business Overview
Figure 44 Capgemini: Company Snapshot
Table 225 Capgemini: Solutions/Services Offered
12.2.10 Mphasis
Table 226 Mphasis: Business Overview
Figure 45 Mphasis: Company Snapshot
Table 227 Mphasis: Solutions/Services Offered
12.2.11 Databrics
Table 228 Databrics: Business Overview
Table 229 Databrics: Solutions/Services Offered
Table 230 Databrics: Deals
12.2.12 Mostly Ai
Table 231 Mostly Ai: Business Overview
Table 232 Mostly Ai: Solutions/Services Offered
Table 233 Mostly Ai: Deals
12.2.13 Tonic
Table 234 Tonic: Business Overview
Table 235 Tonic: Solutions/Services Offered
Table 236 Tonic: Deals
12.2.14 Md Clone
Table 237 Md Clone: Business Overview
Table 238 Md Clone: Solutions/Services Offered
Table 239 Md Clone: Deals
12.2.15 Tcs
12.3 Startups/Smes
12.3.1 Hazy
12.3.2 Synthesia
12.3.3 Synthesized
12.3.4 Facteus
12.3.5 Anyverse
12.3.6 Neurolabs
12.3.7 Rendered Ai
12.3.8 Gretel
12.3.9 Oneview
12.3.10 Genrocket
12.3.11 Y Data
12.3.12 Cvedia
12.3.13 Syntheticus
12.3.14 Anylogic
12.3.15 Bifrost Ai
12.3.16 Anonos
*Details on Business Overview, Products Offered, Recent Developments, Analyst's View, Right to Win, Strategic Choices Made, Weaknesses and Competitive Threats Might Not be Captured in Case of Unlisted Companies.

13 Adjacent and Related Markets
13.1 Natural Language Processing Market
13.1.1 Market Definition
13.1.2 Market Overview
13.1.3 Natural Language Processing Market, by Component
Table 240 Natural Language Processing Market, by Component, 2016-2021 (USD Million)
Table 241 Natural Language Processing Market, by Component, 2022-2027 (USD Million)
13.1.4 Natural Language Processing Market, by Type
Table 242 Natural Language Processing Market, by Type, 2016-2021 (USD Million)
Table 243 Natural Language Processing Market, by Type, 2022-2027 (USD Million)
13.1.5 Natural Language Processing Market, by Deployment Mode
Table 244 Natural Language Processing Market, by Deployment Mode, 2016-2021 (USD Million)
Table 245 Natural Language Processing Market, by Deployment Mode, 2022-2027 (USD Million)
13.1.6 Natural Language Processing Market, by Organization Size
Table 246 Natural Language Processing Market, by Organization Size, 2016-2021 (USD Million)
Table 247 Natural Language Processing Market, by Organization Size, 2022-2027 (USD Million)
13.1.7 Natural Language Processing Market, by Application
Table 248 Natural Language Processing Market, by Application, 2016-2021 (USD Million)
Table 249 Natural Language Processing Market, by Application, 2022-2027 (USD Million)
13.1.8 Natural Language Processing Market, by Technology
Table 250 Natural Language Processing Market, by Technology, 2016-2021 (USD Million)
Table 251 Natural Language Processing Market, by Technology, 2022-2027 (USD Million)
13.1.9 Natural Language Processing Market, by Vertical
Table 252 Natural Language Processing Market, by Vertical, 2016-2021 (USD Million)
Table 253 Natural Language Processing Market, by Vertical, 2022-2027 (USD Million)
13.1.10 Natural Language Processing Market, by Region
Table 254 Natural Language Processing Market, by Region, 2016-2021 (USD Million)
Table 255 Natural Language Processing Market, by Region, 2022-2027 (USD Million)
13.2 Artificial Intelligence Market
13.2.1 Market Definition
13.2.2 Market Overview
13.2.3 Artificial Intelligence Market, by Offering
Table 256 Artificial Intelligence Market, by Offering, 2016-2021 (USD Billion)
Table 257 Artificial Intelligence Market, by Offering, 2022-2027 (USD Billion)
13.2.4 Artificial Intelligence Market, by Technology
Table 258 Artificial Intelligence Market, by Technology, 2016-2021 (USD Billion)
Table 259 Artificial Intelligence Market, by Technology, 2022-2027 (USD Billion)
13.2.5 Artificial Intelligence Market, by Deployment Mode
Table 260 Artificial Intelligence Market, by Deployment Mode, 2016-2021 (USD Billion)
Table 261 Artificial Intelligence Market, by Deployment Mode, 2022-2027 (USD Billion)
13.2.6 Artificial Intelligence Market, by Organization Size
Table 262 Artificial Intelligence Market, by Organization Size, 2016-2021 (USD Billion)
Table 263 Artificial Intelligence Market, by Organization Size, 2022-2027 (USD Billion)
13.2.7 Artificial Intelligence Market, by Business Function
Table 264 Artificial Intelligence Market, by Business Function, 2016-2021 (USD Billion)
Table 265 Artificial Intelligence Market, by Business Function, 2022-2027 (USD Billion)
13.2.8 Artificial Intelligence Market, by Vertical
Table 266 Artificial Intelligence Market, by Vertical, 2016-2021 (USD Billion)
Table 267 Artificial Intelligence Market, by Vertical, 2022-2027 (USD Billion)
13.2.9 Artificial Intelligence Market, by Region
Table 268 Artificial Intelligence Market, by Region, 2016-2021 (USD Billion)
Table 269 Artificial Intelligence Market, by Region, 2022-2027 (USD Billion)
14 Appendix
14.1 Discussion Guide
14.2 Knowledgestore: The Subscription Portal
14.3 Customization Options

Companies Mentioned

  • Anonos
  • Anylogic
  • Anyverse
  • Aws
  • Bifrost Ai
  • Broadcom
  • Capgemini
  • Cvedia
  • Databrics
  • Facteus
  • Genrocket
  • Google
  • Gretel
  • Hazy
  • Ibm
  • Informatica
  • Md Clone
  • Microsoft
  • Mostly Ai
  • Mphasis
  • Neurolabs
  • Nvidia Corporation
  • Oneview
  • Openai
  • Rendered Ai
  • Synthesia
  • Synthesized
  • Syntheticus
  • Tcs
  • Tonic
  • Y Data

Methodology

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Table Information

Report AttributeDetails
No. of Pages261
PublishedJune 2023
Forecast Period2023 - 2028
Estimated Market Value ( USD ) in 2023 $ 0.3 Billion
Forecasted Market Value ( USD ) by 2028 $ 2.1 Billion
Compound Annual Growth Rate45.7%
Regions CoveredGlobal
No. of Companies Mentioned31

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