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Data Annotation Tools Market worth US$ 6,450.0 Million by 2027 - Exclusive Report by The Insight Partners
The global data annotation tools market was valued US$ 897.5 Mn in 2020 and is expected to reach US$ 6,450.0 Mn by 2027 with a CAGR growth rate of 32.54% in the forecast period from 2019 to 2027.Get Sample PDF Copy of Latest Research on Data Annotation Tools Market @ https://www.theinsightpartners.com/sample/TIPRE00008379/?utm_source=OpenPR&utm_medium=10452
The process of data annotation includes labeling of data which makes it usable for machine learning. Data annotation tools are an important tool for data scientists as they make use of the labelled data with machine learning algorithms. Data can be in any form such as images (from cars, phones, or medical instruments), text (in English, Spanish, Chinese, or any other language), audio and video. There are different types of annotation techniques like polygon annotation, semantic segmentation, bounding box annotation, landmark annotation, polylines annotation and 3D point cloud annotation. In house teams can label the data if it is a small set, but this can be time consuming. When data is huge outsourcing it to companies like Precise BPO Solution who can handle millions of annotations in a week could save time. Further, investments by various market players in data annotation techniques in order to offer high quality labelled data are predictable to play a significant role in the near future.
Leading Data Annotation Tools Market Players:
• Appen Limited
• CloudFactory Limited
• Cogito
• Deep Systems
• Google LLC
• Labelbox, Inc
• LIGHTTAG
• Tagtog Sp. z o.o.
• PLAYMENT INC.
• SCALE AI, INC.
Market Insights-Data Annotation Tools Market
Increasing Organic Development by Market Players
Crowdsourcing cannot be considered as an option while evaluating, updating, and removing data from structured documents such as medical reports, or related contracts. A better understanding of the information is required to accurately annotate and mark AI details. Data preparation, annotation, and labeling are essential for training AI and machine learning models, which has, in turn, propelled the demand for data annotation tools. Owing to the increasing demand for data annotation, market players are taking part in various organic developments in the field of artificial intelligence, machine learning, image recognition, and robotics for training data. For instance, in April 2019, CloudFactory, one of the global leaders in managing workforce solutions for artificial intelligence (AI), launched a solution and partnered with AI technology providers Hivemind, Labelbox, and Dataloop to tag, label, or annotate data. Similarly, in June 2019, Innodata Inc., founded in 1988, launched data annotation and labeling solutions for enterprises requiring complex training data in AI, which would, in turn, help in managing data annotation and labeling services in key industries such as financial services, legal, healthcare, and pharma.
The report segments the global data annotation tools market as follows:
Global Data Annotation Tools Market - By Type
• Text
• Image
• Others
Global Data Annotation Tools Market - By Annotation Type
• Manual
• Semi-Supervised
• Automatic
Global Data Annotation Tools Market - By End User
• Automotive
• Government
• Healthcare
• Financial Services
• Retail
• IT and Telecom
• Others
Furthermore, Appen (Australia) acquires Figure Eight (San Francisco) for ~US$ 300 million. Figure Eight has machine learning software platform that uses highly automated tools to transform unlabeled text, image, audio, and video data into high-quality AI training data. This acquisition will enhance the development of high-quality, human annotated datasets for machine learning and artificial intelligence; thus, increasing investments by the market players is likely to propel the market growth during the forecast period.
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Drivers & Constraints:
The Data Annotation Tools Market rests united with the incidence of leading players who keep funding to the market's growth significantly every year. The report studies the value, volume trends, and the pricing structure of the market so that it could predict maximum growth in the future. Besides, various suppressed growth factors, restraints, and opportunities are also estimated for the advanced study and suggestions of the market over the assessment period.
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