The global data collection and labeling market size is expected to reach USD 17.10 billion by 2030, expanding at 28.9% CAGR from 2023 to 2030, according to a new report by Grand View Research, Inc. Data collection and labeling refers to the collection of datasets from various sources and labeling them based on their nature. This includes categorizing them by data type, and features. Data gathering and its annotation, combined with AI technology, have created valuable growth opportunities in several verticals, such as gaming, social networking, and e-commerce.
For instance, Twitter and Facebook, two major platforms of social networking, have benefited from image-processing technology in audience engagement. Companies use data labeling platforms to identify raw data for the machine learning model. Text, movies, audio, and other items are raw data. For instance, in May 2022, Heartex, Inc., an annotation tool and data labeling platform provider announced a USD 25 million Series A fundraising round. The funds will go toward its AI-driven open-source data labeling platform. The platform aims to assist in labeling workflows for various AI use cases, and it includes capabilities for reporting, data quality control, and analytics.
The advent of digital capturing devices, particularly cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of images and videos. Much visual and digital information is being captured and shared through several applications, websites, social networks, and other digital channels. Several businesses have leveraged this online content to deliver more innovative and better customer services using data annotation. For instance, Scale AI, Inc., a U.S.-based tech start-up provides valuable data labeling services to its autonomous driving customers, including Waymo LLC; Lyft, Inc.; Zoox; and Toyota Research Institute.
However, data cleaning remains a significant challenge involved in data labeling. Also, considering the time, complexity, and cost associated with developing machine learning models, many companies may need more resources to produce acceptable and accurate results. Therefore, several companies are taking strategic initiatives to expand their business in artificial intelligence-based data gathering. For instance, in July 2020, Microsoft acquired Orions Digital Systems, Inc., a U.S.-based data management solutions provider, to boost its Dynamics 365 Connected Store capabilities. This acquisition is anticipated to increase the use of computer vision and IoT sensors to help retailers better understand customer behavior and manage their physical spaces.
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Automated image organization offered by cloud-based applications and telecom companies is one of the most popular uses of data gathering that has improved the user experience and draws the attention of customers toward this technology
Several benefits, such as better security and automation of identification, encourage the implementation of facial recognition at significant public spaces or events
The advent of large-scale cloud-hosted AI and machine learning platforms offered by tech giants has led to the implementation of data annotation with multiple functions, such as facial recognition, object recognition, and landmark detection
The growing integration of digital image processing and mobile computing platforms in various digital shopping and document verification applications is propelling the market growth
For this report, Grand View Research has segmented the global data collection and labeling market based on data type, vertical, and region:
Data Collection & Labeling Data Type Outlook (Revenue, USD Million, 2017 - 2030)
Data Collection & Labeling Vertical Outlook (Revenue, USD Million, 2017 - 2030)
Retail & E-Commerce
Data Collection & Labeling Regional Outlook (Revenue, USD Million, 2017 - 2030)
Middle East and Africa (MEA)
List of Key Players of Data Collection And Labeling Market
Globalme Localization Inc.
Global Technology Solutions
Scale AI, Inc.
Trilldata Technologies Pvt Ltd
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