The North America Synthetic Data Generation Market would witness market growth of 32.6% CAGR during the forecast period (2022-2028).
Artificial data can aid in training and developing models prior to the availability of real data, hence reducing expenses. The adoption of synthetic data by AI players has risen throughout emerging and developed economies. In 2021, for instance, research conducted by Synthesis AI in cooperation with Vanson Bourne indicated that a significant proportion of IT decision-makers view synthetic data as a key to being competitive.
Executives in the IT sector will likely rely on artificial data to improve data quality and boost efficiency. In its early stage, synthetic data generation is anticipated to increase access, restrict costs, and reduce the time required to build AI models across all industry verticals, like automotive and healthcare. Businesses require synthetic data for three reasons viz. product testing, privacy, as well as training machine learning algorithms.
In addition, industry leaders have begun to emphasize the significance of data-centric methods to AI/ML model building, to which synthetic data can contribute substantial value. When picking a privacy-enhancing technology, businesses confront a trade-off between data privacy as well as data utility. Before investing, they must therefore define the use case's priorities. Synthetic data does not include any personally identifiable information; it is a sample of data with a distribution similar to that of the real data.
According to the Census Bureau of the United States, several products from the Longitudinal Employer-Household Dynamics program utilize synthetic data, such as the LEHD, the on the Map web application, the Post-Secondary Employment Outcomes, Origin-Destination Employment Statistics, Explorer data product, and the Veterans Employment Outcomes (VEO) Explorer. All of these factors are increasing the utilization of synthetic data throughout regional countries.
The US market dominated the North America Synthetic Data Generation Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $244,459.3 Thousands by 2028.The Canada market is poised to grow at a CAGR of 35.7% during (2022 - 2028). Additionally, The Mexico market would witness a CAGR of 34.5% during (2022 - 2028).
Based on Application, the market is segmented into Natural Language Processing, Data Protection, Predictive Analytics, Computer Vision Algorithms and Data Sharing & Others. Based on Offering, the market is segmented into Fully Synthetic Data, Partially Synthetic Data and Hybrid Synthetic Data. Based on Data Type, the market is segmented into Tabular Data, Text Data, Image & Video Data and Others. Based on Modeling Type, the market is segmented into Agent-based Modeling and Direct Modeling. Based on End-use, the market is segmented into Healthcare & Life sciences, IT & Telecommunication, Transportation & Logistics, Retail & E-commerce, BFSI, Consumer Electronics and Manufacturing & Others. Based on countries, the market is segmented into U.S., Mexico, Canada, and Rest of North America.
Free Valuable Insights: The Global Synthetic Data Generation Market is Predict to reach $880.2 Million by 2028, at a CAGR of 34.1%
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Kinetic Vision, Inc. (Deep Vision Data), MOSTLY AI Solutions MP GmbH, Synthesis AI, Inc., Statice GmbH, YData, Ekobit d.o.o, Hazy Limited, Kymera-labs, MDClone Limited, and Neuromation.
By Application
By Offering
By Data Type
By Modeling Type
By End-use
By Country
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