Data Collection and Labeling Market Status and Prospect 2022-2030

Data collection and labeling technologies and tools are extensively used in machine learning applications. These tools form a key part of the development of machine learning and artificial intelligence products. They help in extracting valuable insights from a vast collection of data. The huge data repository is characteristics of social media websites, visual websites, and wide spectrum of emerging digital marketing media platforms. Additionally, they also form a part of spam detection techniques. Thus, the data collection and labeling market has evolved on the back of the need for gaining business insights for applications such as robotics, drones, and autonomous vehicle systems.

Key application areas are in healthcare, government, and automotive sectors. One of the key objectives of such data collection and labeling is meeting the needs of security and surveillance. An example is the use of data collection technologies for facial recognition used by law enforcement agencies.

The study on the data collection and labeling market strives to offer all-encompassing assessment of key demand trends, consumer insights, technological advances, and prospects in various end-use industries. The research offers insights into the share and size of various segments including the regional ones during the forecast period of 2022 – 2030.

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Data Collection and Labeling Market: Key Trends         

Strides in the data collection and labeling market are bolstered by the growing application of machine learning tools and algorithm in commercial and research applications. The growing role of garnering insights from vast volumes of data sets for national security and surveillance is boosting the market. The demand has also been spurred by the prospects of such data collection and labelling in reducing the chances of phishing and spamming, especially in government sector.

One promising avenue has come from measuring emotional contagion in social media, where data collection and labelling has held high prospects. Growing popularity of Twitter and Facebook has also fueling the demand. However, the prospect of the market in social-media-based micro-communications is relatively new. Rise in avenues for proliferation of data offers a huge undercurrent to the expansion of the data collection and labelling market.

Growing demand for cloud-based media services has also spurred prospects in the data collection and labeling market. The application has also risen on the back of strides being made in digital marketing channels. Ecommerce is source of vast volumes of data that need to be labeled for extracting business insights.

Data Collection and Labeling Market: Competitive Analysis and Key Developments

Companies engaged in AI software development and machine learning systems have been leaning on expanding their customer base in the data collection and labeling market. They are getting into strategic mergers, acquisitions, and partnerships to meet the demands of a wide customer base. Several players are tapping into the recently emerging revenue streams in the autonomous vehicle system market. E-commerce companies are keen on adopting machine learning systems that leverage the techniques of data collection and labeling.

Some of the key companies aimed at expanding their stakes in the data collection and labeling market are Playment Inc., Appen Limited, Trilldata Technologies Pvt., Ava Labs, Dobility, Inc., Labelbox, Inc., Alegion, Global Technology Solutions, and Globalme Localization Inc.

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Data Collection and Labeling Market: Regional Assessment

On the other hand, proliferating volumes of data in Asia Pacific has been due to the extensive use of smart devices. Burgeoning social media users has also boosted opportunities in the regional market.

This study by TMR is all-encompassing framework of the dynamics of the market. It mainly comprises critical assessment of consumers’ or customers’ journeys, current and emerging avenues, and strategic framework to enable CXOs take effective decisions.