Synthetic Data Generation Market Research Report: Information By Component (Solution And Services), Deployment Mode (On-Premise and Cloud), Data Type (Tabular Data, Text Data, Image and Video Data and Others), Application (AI Training and Development, Test Data Management, Data Sharing and Retention, Data Analytics), Industry Vertical (BFSI, Healthcare & Life Sciences, Transportation and Logistics, Government & Defense, IT and Telecommunication, Manufacturing, Media & Entertainment And Others) Regions - Forecast Till 2032

Synthetic Data Generation Market Overview

Synthetic Data Generation Market Size was valued at USD 0.25 Billion in 2022. The synthetic data generation market industry is projected to grow from USD 0.36 Billion in 2023 to USD 7.67 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 46.30% during the forecast period (2023 - 2032). Increasing concerns with respect to the data privacy and growing the need for robust AI and machine learning models is the key market drivers enhancing the market growth.

Figure1: Synthetic Data Generation Market, 2018 - 2032 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Synthetic Data Generation Market Trends

The rising awareness of data privacy issues is driving the market CAGR for the development of synthetic data. Protecting people's privacy rights has become of the utmost importance in the age of ongoing data gathering and processing. As a result, data privacy laws have been put in place to ensure that corporations handle personal data responsibly and securely. Examples include the General Data Protection Regulation (GDPR) of the European Union and the California Consumer Privacy Act (CCPA). During the projected period, this elevated worry about data privacy is anticipated to drive the market for synthetic data production.

Organizations are increasingly required to adhere to strict data privacy laws. In particular, GDPR establishes strict rules governing the handling of personal data, requiring explicit agreement for data processing, giving people the right to access and remove their data, and requiring strict data security measures. There is a chance of receiving hefty fines for breaking these rules. As a result, organizations are increasingly using synthetic data to conduct data-driven activities without suffering the legal and financial repercussions associated with improper treatment of personal data. Organizations can create legitimate datasets using synthetic data that accurately reflect the statistical properties of real data while excluding any personally identifiable information (PII), guaranteeing compliance with privacy laws.

Additionally, the development of machine learning (ML) and artificial intelligence (AI) has increased the demand for data privacy. These cutting-edge technologies rely heavily on the quality of their training data, which has a direct impact on how effective they are. Organizations may create a variety of training datasets that abide by privacy regulations for AI and ML models thanks to synthetic data. As a result, they can maintain the robustness and accuracy of their models while protecting the privacy of the people whose data were used to train the models. The market's growth is projected to be fueled by this combined benefit of improving data quality and assuring privacy adherence within the predicted timeframe. Thus, driving the Web3 in E-Commerce & Retail market revenue.

Synthetic Data Generation Market Segment Insights

Synthetic Data Generation Component Insights

The Synthetic Data Generation Market segmentation, based on component includes solution and services. The solution segment dominated the market in the Synthetic Data Generation Market. Businesses are able to improve the precision and sturdiness of their AI and ML models thanks to synthetic data solutions, which offer a reliable supply of this data.

Figure 2: Synthetic Data Generation Market, by Distribution channel, 2022 & 2032 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Synthetic Data Generation Deployment Mode Insights

The Synthetic Data Generation Market segmentation, based on deployment mode, includes on-premise and cloud. The on-premise segment held the largest market revenue share. This is because latency and performance optimization are becoming more and more important for applications that need to generate data in real-time or very close to real-time.

Synthetic Data Generation Data Type Insights

The Synthetic Data Generation Market segmentation, based on data type, includes tabular data, text data, image and video data and others. The tabular data segment held the largest market revenue share. Due to its versatility, tabular data has become a crucial component in decision-making in a variety of fields, including banking, healthcare, retail, and other areas.

Synthetic Data Generation Application Insights

The Synthetic Data Generation Market segmentation, based on application, includes AI training and development, test data management, data sharing and retention, data analytics and others. Throughout the anticipated period, the test data management segment dominated the market. The expansion of this market will be fueled by the need for high-quality, diverse, and analytical data for testing and validation goals.

Synthetic Data Generation Industry Vertical Insights

The Synthetic Data Generation Market segmentation, based on industry vertical, includes BFSI, healthcare & life sciences transportation and logistics, government & defense, IT and telecommunications, manufacturing, media & entertainment and others. The BFSI segment dominated the market in 2022. Fintech's development and the digitalization of financial services have created an environment where quick innovation is crucial to preserving a competitive edge.

Synthetic Data Generation Regional Insights

By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North America synthetic data generation market dominated this market in 2022 (45.80%). This is due to the region's increasing need for diverse, high-quality training data to create and test these AI and ML models. Additionally, the growing emphasis on data security and privacy, especially in light of legislation, is probably going to assist the expansion of this market. Further, the U.S. synthetic data generation market held the largest market share, and the Canada synthetic data generation market was the fastest growing market in the North America region.

Further, the major countries studied in the market report are The U.S., Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.

Figure 3: SYNTHETIC DATA GENERATION MARKET SHARE BY REGION 2022 (USD Billion)

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Europe synthetic data generation market accounts for the second-largest market share. This is a result of the region's strict laws governing data privacy as well as a burgeoning tech industry. Further, the German synthetic data generation market held the largest market share and the UK synthetic data generation market was the fastest growing market in the European region

The Asia-Pacific synthetic data generation Market is expected to grow at the fastest CAGR from 2023 to 2032. This is because more and more advanced technologies are being adopted in the area. Moreover, China’s synthetic data generation market held the largest market share, and the Indian synthetic data generation market was the fastest growing market in the Asia-Pacific region.

Synthetic Data Generation Key Market Players & Competitive Insights

Leading market players are investing heavily in research and development in order to expand their product lines, which will help the Synthetic Data Generation market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their global footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, synthetic data generation industry must offer cost-effective items.

Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the global synthetic data generation industry to benefit clients and increase the market sector. In recent years, the synthetic data generation industry has offered some of the most significant advantages to medicine. Major players in the synthetic data generation market, including Meta, Synthesis AI, CVEDIA Inc., Gretel Labs, Mostly AI, NVIDIA Corporation, Microsoft Corporation, Datagen, Amazon.com, Inc., IBM Corporation and others, are attempting to increase market demand by investing in research and development operations.

A well-known firm is NVIDIA Corp (NVIDIA), which specializes in creating and designing system-on-a-chip, central computing, and graphics processing units. Its product line serves a variety of industries, such as the gaming industry, data centers, professional visualization, and the automotive industry. Design and visualization, data center and cloud computing, high-performance computing, edge computing, and autonomous cars are all included in NVIDIA's product offerings. The business offers products tailored for expert visual designers, gamers, academics, and developers under brands like Quadro, GeForce NOW, GeForce, vGPU, SHIELD, JESTON, DOCA, and Bluefield. Engineering, architecture, construction, cybersecurity, internet, energy, healthcare and life sciences, financial services, gaming, robotics, education, media and entertainment, manufacturing, retail, telecommunications, and transportation are just a few of the diverse industries that NVIDIA supports. The corporation, whose headquarters are in Santa Clara, California, in the United States, has created a presence throughout the Americas, Asia-Pacific, and Europe.

Microsoft Corp., a business with its main office in Redmond, Washington, was established in 1975 and is heavily involved in the creation and delivery of software, services, products, and gadgets. There were around 221,000 full-time employees working for the corporation as of June 30, 2022, with 122,000 of them situated in the US and 99,000 elsewhere. Productivity and Business Processes, Intelligent Cloud, and More Personal Computing are the three distinct business segments in which Microsoft works. A wide range of products and services covering communication, productivity, and information services, designed for different devices and platforms, are included in the Productivity and Business Processes section. The company's public, private, and hybrid server products and cloud services, on the other hand, are the main emphasis of the Intelligent Cloud sector and help modern corporate operations. Last but not least, the More Personal Computing section focuses on goods and services created to satisfy the requirements and preferences of end users, programmers, and IT specialists across all categories of devices. Operating systems, cross-device productivity apps, server apps, business solution apps, desktop and server management tools, software development tools, video games, personal computers, tablets, gaming and entertainment consoles, as well as other intelligent devices and related accessories are all part of the wide range of products that Microsoft offers.

Key Companies in the Synthetic Data Generation market include

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  Meta

  
  


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  Synthesis AI

  
  


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  CVEDIA Inc.

  
  


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  Gretel Labs

  
  


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  Mostly AI

  
  


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  IBM

  
  


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  NVIDIA Corporation

  
  


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  Microsoft Corporation

  
  


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  Datagen

  
  


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  Amazon.com, Inc.

  
  

Synthetic Data Generation Industry Developments

January 2022: Austrian synthetic data startup MOSTLY AI has announced the successful completion of a $25 million Series B funding round, with participation from Citi Ventures and top British venture capital firm Molten Ventures. The company has headquarters in New York City and already has a presence in both the European and American markets, where it seeks to commercialize synthetic data.

Synthetic Data Generation Market Segmentation

Synthetic Data Generation Component Outlook

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  Solution

  
  


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  Services

  
  

Synthetic Data Generation Deployment Mode Outlook

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  On-Premise

  
  


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  Cloud

  
  

Synthetic Data Generation Data Type Outlook

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  Tabular Data

  
  


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  Text Data

  
  


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  Image and Video Data

  
  


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  Others

  
  

Synthetic Data Generation Application Outlook

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  AI Training and Development

  
  


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  Test Data Management

  
  


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  Data Sharing and Retention

  
  


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  Data Analytics

  
  


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  Others

  
  

Synthetic Data Generation Industry Vertical Outlook

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  BFSI

  
  


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  Healthcare and Life Sciences

  
  


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  Transportation and Logistics

  
  


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  Government and Defense

  
  


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  IT and Telecommunication

  
  


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  Manufacturing

  
  


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  Media and Entertainment

  
  


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  Others

  
  

Synthetic Data Generation Regional Outlook