Pune, Aug. 11, 2023 (GLOBE NEWSWIRE) -- “As per the SNS Insider report, the market for Synthetic Data Generation Market reached US$ 165.9 Million in 2022. It is projected to attain US$ 1874.11 Million by 2030, exhibiting a remarkable CAGR of 35.4% during the forecast period from 2023 to 2030.”
Synthetic Data Generation Market Overview
Synthetic data generation involves creating artificial datasets that mimic the statistical properties and patterns of real data without containing any actual information from the original data sources. It's commonly used when sharing, testing, or training with sensitive or proprietary data isn't feasible or ethical, yet a representative dataset is required. This technique finds applications in various fields, including machine learning, data analysis, and privacy protection. Synthetic data is generated using algorithms that model the underlying distribution and relationships of the original data.
Market Analysis
The synthetic data generation market is experiencing significant growth due to a variety of factors that cater to the needs of industries reliant on data-driven decision-making and machine learning. With increasing regulations like GDPR and CCPA, companies are finding it challenging to share and use real user data for testing and development. Synthetic data offers a solution by allowing them to generate data that mimics real data without compromising privacy. As machine learning models become more complex, they require diverse and large datasets for training. Synthetic data provides a way to generate vast amounts of diverse data, enabling more accurate and robust model training. Many real datasets suffer from class imbalance, where some classes have significantly fewer samples than others. Synthetic data can be used to balance out the dataset and prevent biases in model training.
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Major Players Covered in this Report are:
- Amazon.com, Inc.
- Microsoft Corporation
- Gretel Labs
- Mostly AI
- NVIDIA Corporation
- CVEDIA Inc.
- Synthesis AI
- IBM Corporation
- Datagen
- Meta & Other Players
Impact of Recession on Synthetic Data Generation Market Growth
The impact of a recession on the synthetic data generation market is multifaceted. While the immediate effects could lead to reduced demand and constrained R&D budgets, the market's ability to offer efficient solutions, cater to resilient industries, and attract smaller businesses could contribute to its resilience in the long run. As with any industry, adaptability, innovation, and the ability to address evolving market needs will play a crucial role in determining how the market weathers the challenges posed by a recession.
Synthetic Data Generation Market Report Scope:
| Report Attributes | Details |
| Market Size in 2022 | US$ 165.9 Mn |
| Market Size by 2030 | US$ 1874.11 Mn |
| CAGR | CAGR of 35.4 % From 2023 to 2030 |
| Base Year | 2022 |
| Forecast Period | 2023-2030 |
| Historical Data | 2020-2021 |
| Synthetic Data Generation Market: Key Segmentation | • By Data Type (Tabular Data, Text Data, Image, and Video Data, Others) • By Application (AI Training and Development, Test Data Management, Data Sharing and Retention, Data Analytics, Others) • By Industry Vertical (BFSI, Healthcare and Life Sciences, Transportation, Logistics, Government, Defense, IT, Telecommunication, Manufacturing, Others) |
| Key Regional Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Key Growth Drivers | • The market for synthetic data production has new growth potential due to the rising demand for IoT and connected devices. • Increasing demand for data security and privacy, and rising investment in advanced technologies drive the growth of the market. |
Impact of the Russia-Ukraine War
The Russia-Ukraine war's impact on the synthetic data generation market is nuanced and multifaceted. While challenges stemming from data localization and regulatory scrutiny may arise, opportunities for innovation, increased demand, and ethical considerations could also reshape the landscape. As geopolitical events continue to unfold, the market will likely respond and adapt, revealing the complex interplay between technology trends and global affairs.
Key Regional Developments
The global synthetic data generation market is not only influenced by technological advancements and industry-specific demands but also shaped by regional nuances in terms of regulations, cultural attitudes towards data, and market maturity. The dynamics observed in North America, Europe, Asia Pacific, and Latin America highlight the multifaceted nature of this market's evolution, indicating a promising future where synthetic data will play a pivotal role in enabling data-driven innovation across the globe.
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Key Takeaway from Synthetic Data Generation Market Study
- The convergence of the Tabular Data Segment and the BFSI Segment within the realm of synthetic data generation holds immense promise for the data-driven landscape. As machine learning continues to underpin decision-making processes in finance, the assurance of data integrity and security through synthetic data becomes an indispensable asset.
- As technology continues to evolve, organizations that invest in pioneering synthetic data solutions position themselves at the forefront of innovation, driving progress while upholding the tenets of data privacy and security.
Recent Developments Related to Synthetic Data Generation Market
- AuraML, a groundbreaking Synthetic Image Data Platform, has recently secured an impressive $230,000 in pre-seed funding from the Indian Angel Network (IAN), a prominent early-stage investment group.
- Introducing Parallel Domain's latest innovation: Data Lab, a groundbreaking self-serve API designed to revolutionize the field of synthetic data generation. This cutting-edge technology empowers businesses across various industries to harness the power of AI-generated data.
Table of Contents
1. Introduction
2. Research Methodology
3. Market Dynamics
4. Impact Analysis
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Synthetic Data Generation Market, by Data Type
9. Synthetic Data Generation Market, by Application
10. Synthetic Data Generation Market, by Industry Vertical
11. Regional Analysis
12. Company profile
13. Competitive Landscape
14. Use Case and Best Practices
15. Conclusion
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