The Rise of Synthetic Data Generation Market: A $2.1 billion Industry Dominated by Microsoft (US), Google (US), IBM (US) | MarketsandMarkets™

/EIN News/ -- Delray Beach, FL, Feb. 07, 2025 (GLOBE NEWSWIRE) -- MarketsandMarkets forecasts the global Synthetic Data Generation Market size 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 growth of the synthetic data generation market can be attributed to several factors, including increasing concerns about data privacy and security. Also, the cost-effectiveness and time efficiency of generating synthetic data compared to collecting and labeling real-world data will drive the market's growth.

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Synthetic Data Generation Market Dynamics:

Drivers

• Rising adoption of AI and machine learning technologies
• Increasing need for data privacy and compliance

Restraints

• Regulatory and ethical considerations
• Issues related to achieving quality data and realism

Opportunities

• Increasing deployment of large language models
• Growing interest of enterprises in commercializing synthetic images

List of Key Players in Synthetic Data Generation Market:

• Microsoft (US)
• Google (US)
• IBM (US)
• AWS (US)
• NVIDIA (US)
• OpenAI (US)
• Informatica (US)
• Broadcom (US)
• Sogeti (France)
• Mphasis (India)

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Synthetic data is information generated on a computer to augment or replace real data to improve AI models, protect sensitive data, and mitigate bias. Synthetic data allows businesses to address concerns about data privacy and security by generating realistic and representative data without exposing sensitive information. Generating synthetic data is often more cost-effective and time-efficient than collecting and labeling real-world data. It eliminates the need for extensive data collection processes, reducing costs and accelerating development timelines.

Synthetic data enables businesses to generate large volumes of diverse datasets, providing more comprehensive coverage of scenarios and use cases. This scalability and diversity are valuable for training and testing machine learning models. Synthetic data enables businesses to create datasets tailored to specific applications or edge cases that may be challenging to capture with real-world data. This customization helps improve model performance, accuracy, and generalization capabilities.

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By data type, text data to segment to record the highest growth rate  during the forecast period

By data type, the text data segment has the highest growth rate during the forecast period. The increased demand for artificial intelligence (AI) and machine learning (ML) applications requires large amounts of data to train and develop models, thus driving the text data segment.

Among applications, the Test data management segment recorded the second-highest market share during the forecast period.

Under the applications segment, the Test data management segment is expected to have the second-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.

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