Synthetic Data Generation Market Size & Share, by Modelling (Direct, Agent); Offering (Fully, Partially, Hybrid); Data Type (Tabular, Text, Image & Video); Application (AI Training & Development, Test Data Management, Data Sharing & Retention, Data Analytics); Vertical (BFSI, Healthcare & Life Sciences, Transportation & Logistics, Government & Defense, IT & Telecommunication, Manufacturing, Media & Entertainment) - Global Supply & Demand Analysis, Growth Forecasts, Statistics Report 2024-2036

  • Report ID: 5711
  • Published Date: Feb 21, 2024
  • Report Format: PDF, PPT

Global Market Size, Forecast, and Trend Highlights Over 2024-2036

Synthetic Data Generation Market size is expected to reach USD 12.45 Billion by the end of 2036, growing at a CAGR of 35% during the forecast period, i.e., 2024-2036. In the year 2023, the industry size of synthetic data generation was USD 340 Million. AI systems for computer vision and autonomous driving already depend heavily on this developing technology. Car makers may construct realistic datasets and simulated landscapes at scale without actually driving by combining techniques from the film and gaming industries (simulation, CGI) with generative neural networks (GANs, VAEs). In 2021, there was a 3% year-over-year growth in the production of motor cars, with around 80 million vehicles produced worldwide.

In addition, the main corporations planning to expand their portfolios will benefit greatly from the urgency with which privacy legislation, such as GDPR, must be followed. Other growing uses of generated data include ramping up model development and training models in the absence of real data. Artificial data is a valuable resource for training and fostering models prior to the availability of real data while also reducing costs.


Synthetic Data Generation Market
Get more information on this report: Request Free Sample PDF

Synthetic Data Generation Sector: Growth Drivers and Challenges

Growth Drivers

  • Growing Need for Security and Privacy of Data- The need for synthetic data a realistic duplicate of the real data collection with comparable statistical characteristics is driven by the growing privacy hazards associated with gathering real-world statistics. This synthetic data has various benefits in terms of privacy, scalability, and variety and can be utilized in place of genuine data.
    For example, in April 2023, Betterdata, a Singapore-based startup, announced that it would secure confidential data and improve machine learning models by using synthetic data that resembles real-world datasets in terms of structure and characteristics without revealing any personal or sensitive information about an individual.
  • Increased Use of Large Language Models (LLM)- With the aid of enormous datasets, language models are used in the production of several websites and other applications. Large Language Models (LLM) are learning algorithms that assist in the translation, generation, and prediction of text and other types of information. A language model called the Generative Pre-trained Transformer (GPT) uses the GPT-1, GPT-2, and GPT-3 models to generate text data. With 175 million machine learning parameters, GPT-3 is the most sophisticated model and has produced a sizable dataset of conversational data.
    The ongoing creation of websites and other database solutions takes use of the need for language models in a number of sectors, including computing, retail, healthcare, and other industries. Various end users use these language models for code generation, fraud detection, image annotation, text production, and conversational AI.
  • Growth of the Market Was Accelerated by Increasing Use of AI and ML Technologies to Synthesize Complex Database During Pandemic- The increasing adoption of artificial intelligence (AI) and machine learning (ML) technology in several industries, such as banking and financial services, healthcare, media & entertainment, automotive, and others, aids in protecting private data from online dangers. The use of synthetic data promotes internal data sharing inside the company, which greatly aids in the safe storage of extremely complex structural data by adhering to security guidelines. Therefore, during the COVID-19 crisis, the use of synthetic data preserved data privacy and mimicked the statistical characteristics of the operational data without endangering the privacy of an individual or an organization.

Challenges

  • Inaccurate and unrealistic data impedes market expansion- Users can test and share virtual replicas of datasets created using synthetic data production. Furthermore, it is challenging for this method to capture the fine details of specialist models and real-world photographs. Maintaining the synthetic dataset over time is difficult since it relies on real-world data and varies as a result of inventions and advancements. Organizations should therefore routinely verify the accuracy and dependability of the synthetic data.
    This aspect substantially impedes the growth of the synthetic data generation market by degrading the quality and realism of the synthetic data.
  • Lack of maturity in the market is anticipated to impede market growth.
  • The use of phony data poses privacy risks that could impede market expansion.

Synthetic Data Generation Market: Key Insights

Base Year

2023

Forecast Year

2024-2036

CAGR

~ 35%

Base Year Market Size (2023)

 ~ USD 340 Million

Forecast Year Market Size (2036)

 ~ USD 12.45 Billion

Regional Scope

  • North America (U.S., and Canada)
  • Latin America (Mexico, Argentina, Rest of Latin America)
  • Asia-Pacific (Japan, China, India, Indonesia, Malaysia, Australia, Rest of Asia-Pacific)
  • Europe (U.K., Germany, France, Italy, Spain, Russia, NORDIC, Rest of Europe)
  • Middle East and Africa (Israel, GCC North Africa, South Africa, Rest of the Middle East and Africa)
Get more information on this report: Request Free Sample PDF

Synthetic Data Generation Segmentation

Data Type (Tabular Data, Text Data, Image & Video Data)

Based on data type, tabular data in the synthetic data generation market is anticipated to hold largest revenue share of about 50% during the forecast period. Recently, privacy concerns have made it difficult for businesses to get real-life data. Due to these difficulties, synthetic data that resembles real data is produced and can be kept in an organized tabular manner. This increases the need for tabular data, which is anticipated to increase at a notable CAGR over the course of the projected period. Businesses can improve operational data security and privacy by utilizing Generative Adversarial Networks (GANs) to create synthetic tabular data.
Research analysts predict that by 2030, the use of artificial tabular data to train AI models will expand at a rate that is around three times faster than that of real structured data.

Application (AI Training & Development, Test Data Management, Data Sharing & Retention, Data Analytics)

Based on application, test data management segment in the synthetic data generation market is attributed to hold largest share of about 35% during the forecast period. The market will be driven by the requirement for representative, varied, and high-quality data for testing and validation. Synthetic data can help businesses improve the efficacy and efficiency of their testing procedures, which will improve product quality, accelerate time-to-market, and save costs compared to standard test data management techniques. Due to the test data manager's growing requirement for the lowest collection of data for data testing and data masking, this market segment has the biggest share. It also seeks to avert GDPR-related legal issues. Due to the challenge’s businesses face when exchanging data across borders, the corporate data sharing market is expanding significantly.

Our in-depth analysis of the global synthetic data generation market includes the following segments:

     Component

  • Solution
  • Services

     Deployment Mode

  • On-Premise
  • Cloud

     Modelling Type

  • Direct Modelling
  • Agent-Based Modelling

     Offering

  • Fully Synthetic Data
  • Partially Synthetic Data
  • Hybrid Synthetic Data

     Data Type

  • Tabular Data
  • Text Data
  • Image & Video Data

     Application

  • AI Training & Development
  • Test Data Management
  • Data Sharing & Retention
  • Data Analytics

     Vertical

  • BFSI
  • Healthcare & Life Sciences
  • Transportation & Logistics
  • Government & Defense
  • IT & Telecommunication
  • Manufacturing
  • Media & Entertainment

Want to customize this research report as per your requirements? Our research team will cover the information you require to help you take effective business decisions.

Customize this Report

Synthetic Data Generation Industry - Regional Synopsis

North American Market Forecast

Synthetic data generation market in North America region is attributed to hold largest revenue share of about 33% during the forecast period. North America is a centre for technical development, with a particular emphasis on data-driven breakthroughs, AI, and machine learning. Due to the abundance of start-ups, tech firms, and research institutions in this area, there is a strong need for high-quality synthetic data for performing experiments and training AI models. North America is home to an astounding 291 start-up ecosystems among the top 1,000 worldwide. The United States maintains its leadership position with 252 of these coming from the country. Canada, which has its own thriving start-up ecosystem, contributes 39 ecosystems. The market production in this area is further propelled by the existence of significant competitors in the area.

APAC Market Statistics

Synthetic data generation market in Asia Pacific projected to hold second largest revenue share of about 38% during the forecast period. This is a result of the region embracing an increasing number of cutting-edge technologies. In addition, the Asia-Pacific region's synthetic data creation market in China had the most market share, while the market in India was expanding at the fastest rate. Due to growing adoption of AI/ML and cloud-based services across several industries for secure corporate infrastructure, Asia Pacific is expected to develop at the fastest compound annual growth rate.

Research Nester
Synthetic Data Generation Market Size
Get more information on this report: Request Free Sample PDF

Companies Dominating the Synthetic Data Generation Landscape

top-features-companies
    • Microsoft Corporation
      • Company Overview
      • Business Strategy
      • Key Product Offerings
      • Financial Performance
      • Key Performance Indicators
      • Risk Analysis
      • Recent Development
      • Regional Presence
      • SWOT Analysis
    • Google LLC
    • NVIDIA Corporation
    • GenRocket, Inc.
    • Synthesis AI
    • Datagen
    • Hazy Limited.
    • Gretel Labs, Inc.
    • K2view Ltd.
    • Amazon.com, Inc.

In-the-news

In The News

  • By comprehending distracted driving behavior, Seeing Machine Limited and Devant AB, a human-centric synthetic data supplier, worked together to improve transportation safety. Through this collaboration, Seeing Machine's new car cabin was integrated with Devant's 3D human animation and computer-generated humans, advancing in-cabin sensor technologies.
  • By comprehending distracted driving behavior, Seeing Machine Limited and Devant AB, a human-centric synthetic data supplier, worked together to improve transportation safety. Through this collaboration, Seeing Machine's new car cabin was integrated with Devant's 3D human animation and computer-generated humans, advancing in-cabin sensor technologies.

Author Credits:  Abhishek Verma, Hetal Singh


  • Report ID: 5711
  • Published Date: Feb 21, 2024
  • Report Format: PDF, PPT

Frequently Asked Questions (FAQ)

Increasing use of AI and ML technologies to synthesize complex database are the major factors driving the growth of the synthetic data generation market.

The market size of synthetic data generation is anticipated to attain a CAGR of 35% over the forecast period, i.e., 2024 - 2036.

The major players in the market are Google LLC, NVIDIA Corporation, GenRocket, Inc., Synthesis AI, Datagen, Hazy Limited., Gretel Labs, Inc., K2view Ltd., Amazon.com, Inc., and others.

The tabular data segment is anticipated to garner the largest market size by the end of 2036 and display significant growth opportunities.

The market in the North America region is projected to hold the largest market share by the end of 2036 and provide more business opportunities in the future.
Synthetic Data Generation Market Report Scope
  GET A FREE SAMPLE

FREE Sample Copy includes market overview, growth trends, statistical charts & tables, forecast estimates, and much more.

 Request Free Sample Copy

Have questions before ordering this report?

Inquiry Before Buying