市場調查報告書
商品編碼
1596040
資料收集及標記的全球市場:數據類型·產業·不同地區的預測 (~2032年)Global Data Collection and Labelling Market Research Report By Data Type, by Vertical, and By Region Forecast Till 2032 |
資料收集和標籤市場規模預計將從 2023 年的 27.018 億美元增長到 2024 年的 29.841 億美元,預測期內複合年增長率為 29.4%,到 2032 年預計將增長到 234.768 億美元。
資料標註的品質是自動駕駛汽車訓練的關鍵因素。自動駕駛汽車需要最高品質的註解來確保可靠性和安全性。準確的數據註釋對於自動駕駛的成功至關重要,因為它可以正確識別道路上的物品和特徵,從而使車輛安全行駛。不正確的數據標籤可能會嚴重影響研究和製造階段,造成瓶頸並危及自動駕駛汽車的功能和安全。資料驗證是自動駕駛車輛資料註釋過程中的關鍵步驟。這確保了註釋資料準確、完整併且與正在訓練的演算法相關。自動駕駛汽車資料註釋品質的願景是使用先進的註釋技術和自動化流程來提高安全性和準確性。透過對細分市場提出新的見解,提高自動駕駛系統的安全性和可靠性。
區域洞察
北美包括美國、加拿大和墨西哥。數據收集和標記在北美正在迅速增加。數據註釋和標記在充滿大公司並迅速採用新技術的行業中迅速普及。正在建構的人工智慧和機器學習模型的複雜性日益增加,要求公司外包這些服務以滿足其資料處理要求。
亞太地區,特別是中國、日本和印度等國家,近年來各產業對人工智慧和機器學習 (ML) 的使用急劇增加。隨著這些技術的實施,對資料擷取和註釋的需求正在呈指數級增長。
本報告提供全球資料收集及標記的市場調查,彙整市場定義和概要,市場成長的各種影響因素分析,市場規模的轉變·預測,各種區分·地區/各主要國家的明細,競爭環境,主要企業簡介等資訊。
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