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Synthetic Data Generation Market Size, Share & Trends Analysis Report By Data (Tabular Data, Text Data, Image & Video Data, Others), By Modeling, By Offering, By Application, By End Use, By Region, And Segment Forecasts, 2024 - 2030
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Synthetic Data Generation Market Growth & Trends:

The global synthetic data generation market size is expected to reach USD 1,788.1 million in 2030 and is projected to grow at a CAGR of 35.3% from 2024 to 2030. Synthetic data has disrupted most industries with the affordability and accessibility of quality training data. Artificial data has gained ground to boost AI and innovation by minimizing data barriers.

Moreover, the exponential growth of smartphones and other smart devices has contributed to the growth of the industry. For instance, customers will receive an uptick from synthetic data to assess the performance of camera modules and decide the optimal camera placement in the car cabin. With the soaring demand for AI systems, synthetic data generation tools will likely gain traction.

It is worth noting that synthetic data is generally used in tandem with real-world data to test and develop AI algorithms. As companies across industry verticals adopt digitization, industry players are poised to emphasize artificial data to bolster strategies. Synthetic data has the innate ability to enhance the performance of computer vision algorithms to develop intelligent assistants in virtual reality and augmented reality and detect hate speech. Social media platforms, such as Meta (Facebook), could exhibit traction for synthetic data.

For instance, in October 2021, Facebook was reported to have acquired AI. Reverie, a synthetic data startup. It is worth mentioning that in July 2020, AI. Reverie was awarded a USD 1.5 million Phase 2 Small Business Innovation Research (SBIR) contract by AFWERX, an innovation arm of the U.S. Air Force. The company was expected to create synthetic images to train the accuracy of navigation vision algorithms.

The IT & telecommunication sector has shown an increased inclination for artificial data for increased security, scalability, and speed. End-users are likely to seek synthetic data to do away with roadblocks of security and privacy protocols. Some factors, such as advanced privacy-preserving, anonymization, and encryption, have encouraged leading companies to inject funds into synthetic data generation tools.

For instance, in October 2021, Turk Telekom announced infusing funds into four AI-based startups, such as Syntonym, B2Metric, QuantWifi, and Optiyol. Notably, Syntonym is a synthetic data anonymization technology developer.

Asia Pacific is expected to provide lucrative growth opportunities in the wake of the rising prominence of computer vision software, predictive analytics, and natural language processing. For instance, the use of artificial data to organize training data for natural language understanding has grown in popularity. China, Australia, Japan, and India could all be searched for prominently synthetic data to streamline privacy compliance and support client-centered goods and services.

With AI, machine learning, and metaverse counting heavily on large datasets to function effectively, the need for data protection could shift attention towards artificial data. Besides, several data scientists are banking on synthetic data to propel their real-world records and garner actionable insights.

Synthetic Data Generation Market Report Highlights:

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

Chapter 3. Synthetic Data Generation Market Variables, Trends, & Scope

Chapter 4. Synthetic Data Generation Market: Data Estimates & Trend Analysis

Chapter 5. Synthetic Data Generation Market: Modelling Estimates & Trend Analysis

Chapter 6. Synthetic Data Generation Market: Offering Estimates & Trend Analysis

Chapter 7. Synthetic Data Generation Market: Application Estimates & Trend Analysis

Chapter 8. Synthetic Data Generation Market: End Use Estimates & Trend Analysis

Chapter 9. Synthetic Data Generation Market: Regional Estimates & Trend Analysis

Chapter 10. Competitive Landscape

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