市场调查报告书
商品编码
1596040
资料收集及标记的全球市场:数据类型·产业·不同地区的预测 (~2032年)Global Data Collection and Labelling Market Research Report By Data Type, by Vertical, and By Region Forecast Till 2032 |
资料收集和标籤市场规模预计将从 2023 年的 27.018 亿美元增长到 2024 年的 29.841 亿美元,预测期内复合年增长率为 29.4%,到 2032 年预计将增长到 234.768 亿美元。
资料标註的品质是自动驾驶汽车训练的关键因素。自动驾驶汽车需要最高品质的註解来确保可靠性和安全性。准确的数据註释对于自动驾驶的成功至关重要,因为它可以正确识别道路上的物品和特征,从而使车辆安全行驶。不正确的数据标籤可能会严重影响研究和製造阶段,造成瓶颈并危及自动驾驶汽车的功能和安全。资料验证是自动驾驶车辆资料註释过程中的关键步骤。这确保了註释资料准确、完整併且与正在训练的演算法相关。自动驾驶汽车资料註释品质的愿景是使用先进的註释技术和自动化流程来提高安全性和准确性。透过对细分市场提出新的见解,提高自动驾驶系统的安全性和可靠性。
区域洞察
北美包括美国、加拿大和墨西哥。数据收集和标记在北美正在迅速增加。数据註释和标记在充满大公司并迅速采用新技术的行业中迅速普及。正在建构的人工智慧和机器学习模型的复杂性日益增加,要求公司外包这些服务以满足其资料处理要求。
亚太地区,特别是中国、日本和印度等国家,近年来各产业对人工智慧和机器学习 (ML) 的使用急剧增加。随着这些技术的实施,对资料撷取和註释的需求正在呈指数级增长。
本报告提供全球资料收集及标记的市场调查,彙整市场定义和概要,市场成长的各种影响因素分析,市场规模的转变·预测,各种区分·地区/各主要国家的明细,竞争环境,主要企业简介等资讯。
Global Data Collection and Labelling Market Research Report By Data Type (Text, Image/ Video and Audio), by Vertical (IT, Automotive, Government, Healthcare, BFSI, Retail & E-commerce, and Others), and By Region (North America, Europe, Asia-Pacific, Middle East and Africa, South America) Forecast Till 2032
In 2023, the data collection and labelling market was estimated at USD 2,701.8 million. The Data Collection and Labelling Market is expected to expand from USD 2,984.1 million in 2024 to USD 23,476.8 million by 2032, with a compound yearly growth rate (CAGR) of 29.4% over the forecast period (2024-2032). The Data Collection and Labeling market has numerous potentials for both established players and growing entrepreneurs.
The quality of data annotations is an important aspect of self-driving car training. Annotations of the highest quality are required to ensure the dependability and safety of autonomous vehicles. Accurate data annotation is critical to the success of autonomous driving because it allows automobiles to navigate safely by correctly identifying roadside items and features. Inadequate data labeling methods can have a severe impact on the research and manufacturing stages, causing bottlenecks and jeopardizing the functioning and security of self-driving automobiles. Data validation is an important step in the data annotation process for self-driving cars since it ensures accurate and reliable algorithm training. It ensures that the annotated data is accurate, complete, and relevant to the algorithms being trained. The future of data annotation quality in self-driving cars is to improve safety and accuracy using sophisticated annotation techniques and automated processes. Developing fresh insights into market segments can improve the safety and reliability of autonomous driving systems.
The Data Collection and Labelling Market is divided into three segments based on data type: text, image/video, and audio.
The Data Collection and Labelling Market is divided into the following verticals: IT, Automotive, Government, Healthcare, BFSI, Retail & E-commerce, and Others.
Regional insights
North America includes the United States, Canada, and Mexico. North America has seen an upsurge in data collection and tagging. This industry, which has a significant number of large firms and a rapid adoption of novel technology, is where data annotation and tagging have quickly gained traction. The rising complexity of AI and machine learning models being built necessitates organizations outsourcing these services to meet their data processing requirements.
In the Asia-Pacific area, particularly in China, Japan, India, and other nations, the usage of Artificial Intelligence (AI) and Machine Learning (ML) has grown dramatically in recent years across industries. As these technologies are implemented in the real world, the demand for data capture and annotation is increasing at an exponential rate.
For this study, the Europe region includes the United Kingdom, Germany, France, and the rest of Europe. The key drive is projected to be the growing use of AI and ML technologies in Europe, as well as the strong demand for data collecting and labelling services. The region's sectors are gradually adopting AI and ML solutions as advancements in generative AI make the technology more deployable.
The market's leading vendors include Appen Limited, Telcus International, Global Technology Solutions, Alegion, Labelbox, Inc, Reality AI, Globalme Localization Inc, Dobility Inc, Scale AI, and Trilldata Technologies PVT LTD.
GLOBAL DATA COLLECTION AND LABELLING MARKET, BY REGION, 2023 VS 2032 (USD MILLION) 59
SUMMA LINGUAE TECHNOLOGIES 92
APPEN 92
IBM 92
LABELBOX 92
TELUS INTERNATIONAL 92