The image & video data segment is anticipated to contribute significantly toward synthetic data generation market share on the back of soaring demand to boost the database. With researchers emphasizing tabular data, end-user sectors will likely bank on artificial data for data privacy protection. Moreover, in 2019, a team of researchers proposed conditional tabular GAN (CTGAN) to boost the training procedure with mode-specific normalization and address data imbalance, among others. The researchers asserted that users would get data for their projects in tables and time series formats. In October 2020, MIT researchers introduced a set of open-source data generation tools-Synthetic Data Vault. Stakeholders expect the tabular data segment to account for a significant share of the global market, mainly due to bullish demand from researchers. In terms of revenue, the tabular data segment held the largest share of over 40% in 2021. In the nascent stage, synthetic data generation is expected across industry verticals, including automotive and healthcare, to improve access, contain cost, and minimize the time taken to build AI models. Tech executives will likely bank on artificial data to enhance data quality and bolster productivity. For instance, in September 2021, a study from Synthesis AI in collaboration with Vanson Bourne suggested that 89% of technology decision-makers see synthetic data as a key to staying ahead. Prominently, artificial data can help train and foster models before the availability of real data and minimize costs.ĪI stakeholders have exhibited increased synthetic data traction across emerging and advanced economies. Some other expanding applications of the created data include training models amidst a shortage of real data and ramp-up model developments, among others. The urgency to adhere to the privacy laws, including GDPR, will augur well for major companies gearing to foster their portfolios. Artificial data leverages AI and machine learning technology by accessing massive data sets. Moreover, an exponential rise in machine learning has shifted the attention towards synthetic data. Industry players have exhibited an increased demand for simulated data in the wake of a surging penetration of the privacy-preservation solution. Synthetic data is also popular as fake data that can be used in place of real data to train AI models. Industry players are expected to seek synthetic data to address the gap in data provision. Demand for data has become pronounced with a growing footfall of connected devices and IoT, further expediting the need for synthetic data to generate on-demand data. For Instance, in August 2020, the White House reportedly announced an infusion of USD 1 billion in AI and quantum computing. An uptick in the synthetic generation of data following the rising penetration of Artificial Intelligence (AI) has spurred the industry’s growth. The global synthetic data generation market size garnered USD 123.3 million in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 34.8% from 2022 to 2030.
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