Synthetic Data Market Size
Study Period | 2022 - 2029 |
Base Year For Estimation | 2023 |
CAGR (2024 - 2029) | 35.70 % |
Fastest Growing Market | Asia Pacific |
Largest Market | North America |
Market Concentration | Low |
Major Players*Disclaimer: Major Players sorted in no particular order |
Synthetic Data Market Analysis
The Synthetic Data Market is expected to register a CAGR of 35.70% during the forecast period.
Synthetic data generation employs computational methods and simulations to produce data that mirrors the statistical properties of real-world data but does not contain actual real-world observations. This generated data can manifest in various forms, such as text, numbers, tables, or more intricate types like images and videos.
- Synthetic data offers companies a way to navigate around certain regulatory challenges tied to personal data. Privacy and copyright laws safeguard healthcare records, financial data, and online content, complicating large-scale analysis for companies.
- In January 2024, the Science and Technology Directorate (S&T) of the Department of Homeland Security (DHS) has issued a new solicitation. The goal is to find solutions that can generate synthetic data. This synthetic data should model and replicate the shape and patterns of real data, all while ensuring privacy and reducing security risks. Synthetic data holds significant value for the DHS. It enables the Department to train machine learning models in scenarios where real-world data is either unavailable or poses privacy and security concerns. This is especially crucial when the real-world data contains sensitive details, like personally identifiable information (PII).
- As data privacy and compliance regulations like GDPR and CCPA gain prominence, organizations increasingly prioritize the cautious handling of personal data. Synthetic data generation emerges as a viable solution, enabling organizations to produce realistic data that upholds privacy standards and meets regulatory mandates. Consequently, the surging emphasis on data privacy and compliance is propelling the growth of the synthetic data market.
- Synthetic data can be produced on demand and at an almost limitless scale. These tools offer a cost-effective means to augment data volumes and pre-label the generated data for machine learning applications. Users can access structured and labeled data without transforming raw data from scratch. Synthetic data helps mitigate bias in AI training models by counteracting biased language or information. For instance, synthetic data can balance the overall dataset if opinion-based content favors a specific group.
- Technical challenges and quality control restrain market growth. Data quality is crucial in statistics and analytics. Before integrating synthetic data into learning models, verify its accuracy and maintain a baseline quality. Ensuring anonymity might reduce accuracy, affecting quality. Crafting synthetic data requires expertise in techniques, rules, and methods to ensure accuracy and utility.
Synthetic Data Market Trends
Automotive and Transportation End User Segment is Expected to Hold Significant Market Share
- Synthetic data generated by computers is crafted to closely resemble real-world data closely, often targeting specific scenarios or use cases. Its significance is surging across diverse applications. In the automotive industry, synthetic data serves as a pivotal asset, from training algorithms for self-driving cars to evaluating safety features in emerging vehicle models, thereby expediting the development process.
- Synthetic data can simulate various logistics scenarios, helping companies optimize delivery routes and reduce fuel consumption. Synthetic data has emerged as a crucial asset in the evolution of self-driving cars, which depend on sensors and machine learning algorithms for safe and precise operation.
- While industries like Tesla and Waymo leverage extensive real-world data to train their algorithms, numerous other companies face challenges sourcing adequate data. Synthetic data presents a viable solution, enabling developers to generate vast quantities of synthetic data for algorithm training. This capability allows developers to rigorously test and refine their algorithms, minimizing dependence on the limited real-world data.
- The automotive sector initially promotes synthetic data, primarily concentrating on autonomous driving. As the transition from non-semi-autonomous to fully autonomous vehicles, it's imperative to broaden this focus. Areas like in-cabin monitoring and perimeter security monitoring demand attention. Furthermore, synthetic data proves invaluable in training algorithms for recognizing license plates and street signs.
- Engineers can leverage synthetic data to simulate crash scenarios, allowing them to evaluate safety features' effectiveness without real-world testing. This approach enables a more thorough assessment of these safety features.
- Automotive companies leverage synthetic data to create virtual environments that closely resemble real-world driving scenarios. This data aids in training models to adapt to various driving conditions, such as differing weather patterns and traffic scenarios. Additionally, increasing collaborations between synthetic data generators, tech industry players, and automotive firms are fueling the expansion of this segment.
- For instance, in April 2024 partnership between Anyverse, one of the leading synthetic data providers, and Sony Semiconductor Solutions Corporation. This collaboration aims to merge Anyverse's synthetic data platform with Sony's advanced Image Sensor Models.
- The surge in passenger cars significantly boosts the need for synthetic data, driving innovations in safety, efficiency, and user experience. As the automotive landscape evolves, synthetic data will continue to play a critical role in addressing the complexities and challenges that arise. According to OICA, In 2023, China's automotive industry produced approximately 26.1 million passenger cars.
- Synthetic data helps model and analyze passenger behavior, enabling transit agencies to improve schedules and capacity planning based on projected usage. Cities can use synthetic datasets to assess the impact of new transit routes or services, enhancing urban mobility planning.
Asia Pacific Expected to Witness Significant Growth in the Market
- The market is proliferating in the Asia Pacific region during the forecast period. This is due to the rising penetration of advanced technologies such as AI/ML and the growing adoption of cloud-based services among different industries to build secure business infrastructure. Increasing investment in generative AI and the rising focus of companies on AI technology are anticipated to propel the demand for synthetic data generation processes in the Asia Pacific during the forecast period.
- Owing to the presence of multiple market players in the region, the rising number of AI startups, research institutes, and high-tech companies generates demand for high-quality synthetic data to conduct research and experiments. Players in the market make strategic partnerships, which fuels market growth across the region.
- In October 2024, Tata Consultancy Services (TCS), a global leader in IT services, consulting, and business solutions, has announced its partnership with NVIDIA. This collaboration aims to introduce industry-specific solutions, enabling customers to swiftly and broadly adopt artificial intelligence (AI). These offerings will be channeled through TCS' newly established business unit, dedicated to NVIDIA, and operating under the AI.Cloud umbrella. TCS' IoT and Digital Engineering division is collaborating with NVIDIA, accelerate generative AI and deep learning tools like Omniverse for simulations and NVIDIA AI Enterprise for synthetic data.
- Recognizing the importance of interior monitoring in enhancing traffic safety, governments, assessment programs, and consumer tests have compelled vehicle manufacturers to adhere to new regulations in the region.
- Furthermore, in August 2024, the Personal Data Protection Commission of Singapore (PDPC) unveiled its Proposed Guide on Synthetic Data Generation (Guide). This Guide serves as a pivotal resource in the Privacy Enhancing Technology (PET) Sandbox, designed to assist organizations in grasping the techniques and potential uses of Synthetic Data (SD) generation, especially about artificial intelligence (AI).
Synthetic Data Industry Overview
The intensity of competitive rivalry in the market is defined as the competition prevailing in the industry among the established players. The degree of competition depends on various factors affecting the market, such as brand identity, powerful competitive strategy, degree of transparency, and firm concentration ratio.
Some of the major players in the market are MOSTLY AI Solutions MP GmbH, NVIDIA Corporation, Meta, CVEDIA PTE. LTD., and Amazon.com, Inc. among others.
The brand identity associated with the companies has a major influence on the market. As strong brands are synonymous with good performance, long-standing players are expected to have the upper hand.
The firm concentration ratio is projected to grow steadily over the forecast period. High dominance by few market incumbents is expected to be detrimental to the overall profitability of the market. However, the existing market players have a considerable head-start over new entrants. The high prospects and the growing investments and supporting initiatives are expected to increase the competition among the existing market players.
Overall, the degree of competition in the market studied is high during the forecast period.
Synthetic Data Market Leaders
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MOSTLY AI Solutions MP GmbH
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NVIDIA Corporation
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Meta
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CVEDIA PTE. LTD.
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Amazon.com, Inc.
*Disclaimer: Major Players sorted in no particular order
Synthetic Data Market News
- October 2024: GE HealthCare will lead Synthia, a consortium project to evaluate synthetic data generation methods for creating datasets and developing AI algorithms. Partners include Gates Ventures, NovoNordisk, Pfizer, La Fe University, Fraunhofer Institute, and the University of Bologna. The focus is building synthetic datasets to train AI algorithms, addressing challenges like data scarcity, bias, and privacy concerns. However, synthetic data raises questions about the reliability of generation tools and dataset quality.
- March 2024: Rendered.ai, one of the leaders in synthetic data generation, has partnered with Carahsoft Technology Corp., known as The Trusted Government IT Solutions Provider. As part of this collaboration, Carahsoft will act as Rendered.ai's Master Government Aggregator. This partnership enables Carahsoft's reseller partners and contracts like NASA's Solutions for Enterprise-Wide Procurement (SEWP) V, Information Technology Enterprise Solutions – Software 2 (ITES-SW2), National Association of State Procurement Officials (NASPO) ValuePoint, and OMNIA Partners to offer Rendered.ai's advanced synthetic computer vision data subscription services and products to the Public Sector.
Synthetic Data Market Report - Table of Contents
1. INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Buyers
4.2.3 Threat of New Entrants
4.2.4 Threat of Substitutes
4.2.5 Intensity of Competitive Rivalry
5. MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Increasing Demand for Data Privacy and Compliance
5.1.2 Unlimited Data Generation and Bias Reducton
5.2 Market Restraints
5.2.1 Technical Challenges and Quality Control
6. MARKET SEGMENTATION
6.1 By Data Type
6.1.1 Tabular
6.1.2 Text
6.1.3 Image and Video
6.1.4 Other Data Type
6.2 By Offering
6.2.1 Fully Synthetic
6.2.2 Partially Synthetic
6.3 By Application
6.3.1 Data Sharing
6.3.2 AI/ML Training and Development
6.3.3 Test Data
6.3.4 Other Applications
6.4 By End User Vertical
6.4.1 BFSI
6.4.2 Healthcare
6.4.3 Retail and E-commerce
6.4.4 Automotive and Transportation
6.4.5 Government & Defense
6.4.6 IT and ITeS
6.4.7 Industrial & Robotics
6.4.8 Other End User Verticals
6.5 By Geography***
6.5.1 North America
6.5.2 Europe
6.5.3 Asia
6.5.4 Australia and New Zealand
6.5.5 Latin America
6.5.6 Middle East and Africa
7. COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 MOSTLY AI Solutions MP GmbH
7.1.2 NVIDIA Corporation
7.1.3 Meta
7.1.4 CVEDIA PTE. LTD.
7.1.5 Amazon.com, Inc.
7.1.6 IBM
7.1.7 Microsoft
7.1.8 Gretel Labs
7.1.9 Synthesis AI.
7.1.10 GenRocket, Inc.
- *List Not Exhaustive
8. INVESTMENT ANALYSIS
9. FUTURE OUTLOOK OF THE MARKET
Synthetic Data Industry Segmentation
Generative AI models, trained on real-world data samples, create synthetic data. These algorithms initially learn the patterns, correlations, and statistical properties of the sample data. Once trained, the generator produces synthetic data that is statistically identical to the original. While the synthetic data mirrors the original data in appearance and feel, it boasts a significant advantage of not having any personal information.
synthetic data market is segmented by data type (tabular, text, image and video, and other data types), by offering (fully synthetic , partially synthetic), by application (data sharing, AI/ML training and development, test data, other applications), by end user vertical (BFSI, healthcare, retail and e-commerce, automotive and transportation, government & defense, IT and ITes, industrial & robotics, other end user verticals), by geography (North America, Europe, Asia Pacific, Latin America, Middle East and Africa). the report offers market forecasts and size in value (USD) for all the above segments.
By Data Type | |
Tabular | |
Text | |
Image and Video | |
Other Data Type |
By Offering | |
Fully Synthetic | |
Partially Synthetic |
By Application | |
Data Sharing | |
AI/ML Training and Development | |
Test Data | |
Other Applications |
By End User Vertical | |
BFSI | |
Healthcare | |
Retail and E-commerce | |
Automotive and Transportation | |
Government & Defense | |
IT and ITeS | |
Industrial & Robotics | |
Other End User Verticals |
By Geography*** | |
North America | |
Europe | |
Asia | |
Australia and New Zealand | |
Latin America | |
Middle East and Africa |
Synthetic Data Market Research FAQs
What is the current Synthetic Data Market size?
The Synthetic Data Market is projected to register a CAGR of 35.70% during the forecast period (2024-2029)
Who are the key players in Synthetic Data Market?
MOSTLY AI Solutions MP GmbH, NVIDIA Corporation, Meta, CVEDIA PTE. LTD. and Amazon.com, Inc. are the major companies operating in the Synthetic Data Market.
Which is the fastest growing region in Synthetic Data Market?
Asia Pacific is estimated to grow at the highest CAGR over the forecast period (2024-2029).
Which region has the biggest share in Synthetic Data Market?
In 2024, the North America accounts for the largest market share in Synthetic Data Market.
What years does this Synthetic Data Market cover?
The report covers the Synthetic Data Market historical market size for years: 2022 and 2023. The report also forecasts the Synthetic Data Market size for years: 2024, 2025, 2026, 2027, 2028 and 2029.
Synthetic Data Industry Report
Statistics for the 2024 Synthetic Data market share, size and revenue growth rate, created by Mordor Intelligence™ Industry Reports. Synthetic Data analysis includes a market forecast outlook for 2024 to 2029 and historical overview. Get a sample of this industry analysis as a free report PDF download.