The Europe Synthetic Data Generation Market would witness market growth of 33.2% CAGR during the forecast period (2022-2028).
The utility of synthetic data is lower than that of genuine data. However, there are several instances where synthetic data is nearly as valuable as real data. To perform the data synthesis process, businesses can choose from a variety of methodologies, including decision trees, deep learning algorithms, and iterative proportional fitting. They should choose the method based on the requirements for synthetic data and the intended level of data utility for the specific purpose of data generation.
In circumstances when there is no actual data but the data analyst has a thorough grasp of how the distribution of the dataset would appear, the analyst can produce a random sample of any distribution, including Normal, Chi-square, Exponential, t, lognormal, and Uniform. In this method, the utility of synthetic data varies based on the analyst's familiarity with a particular data environment. After data synthesis, the utility of synthetic data should be evaluated by comparing it to actual data.
In the field of artificial intelligence in health care, the focus has been on deductive systems that examine information to discover patterns that would be impossible to implement. However, generative adversarial networks, a new form of artificial intelligence, have evolved more recently (GANs). GANs are a type of artificial intelligence designed to generate high-fidelity false data.
The electronics industry of the regional countries is very robust. According to the Government of the United Kingdom, each year, the electronics industry contributes £16 billion to the British economy. The industry has a robust intellectual property rights framework and legal structure, developed intellectual property rights development, the ability to rapidly deliver products to the market, a large software sector, and a research community comprised of universities, corporations, and industry.
The Germany market dominated the Europe Synthetic Data Generation Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $55,316.5 Thousands by 2028.The UK market is anticipated to grow at a CAGR of 32.1% during (2022 - 2028). Additionally, The France market would exhibit a CAGR of 34.2% 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 Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
Free Valuable Insights: The Global Synthetic Data Generation Market will Hit $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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