Global Data Collection and Labeling Market Report 2022: Rapid Industry Penetration of AI and Machine Learning Engines – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Data Collection and Labeling Market Size, Share, and Trend Analysis Report by Data Type (Audio, Image/Video, Text), by Vertical (Computer , retail and e-commerce), by region and segment forecast, 2022 -2030″ report has been added to from ResearchAndMarkets.com offer.

The global data collection and labeling market size is expected to reach USD 12.75 billion by 2030, according to this report. The market is expected to grow at a CAGR of 25.1% from 2022 to 2030. Data collection and labeling refers to the collection of datasets from online and other sources and their labeling according to their nature, data type and functionality. Data collection and its annotation, combined with AI technology, have created valuable growth opportunities in several verticals, such as gaming, social media and e-commerce.

For example, Twitter and Facebook, two major social networking platforms, have benefited from image processing technology in audience engagement. Companies use data labeling platforms to identify machine learning model raw data. Text, movies, audio and other items are the raw data.

The advent of digital capture 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. A lot of visual and digital information is captured and shared through multiple apps, websites, social media, and other digital channels. Several companies have taken advantage of this available online content to provide smarter and better services to their customers using data annotation. For example, Scale AI, Inc., the US-based tech start-up, has provided valuable data tagging services to its self-driving customers, including Waymo LLC; Lyft, Inc.; Zoox; and the Toyota Research Institute.

However, data cleaning remains a significant challenge related to data labeling. Additionally, given the time, complexity, and cost associated with developing machine learning models, many companies may not have the resources to produce acceptable and accurate results. Therefore, several companies are taking strategic initiatives to expand their business in AI-based data collection. For example, in July 2020, Microsoft acquired Orions Digital Systems, Inc., a US-based data management solutions provider, to bolster its Dynamics 365 Connected Store capabilities. The acquisition is expected to increase the use of computer vision and IoT sensors to help retailers better understand customer behavior and manage their physical spaces.

Highlights of the Data Collection and Labeling Market Report

  • Automated image organization offered by cloud-based applications and telecommunications companies is one of the most popular uses of data collection that has improved user experience and drawn customer attention towards this technology.

  • Several advantages such as better security and automation of identification encourage the implementation of facial recognition in public spaces or important events.

  • The advent of large-scale cloud-hosted AI and machine learning platforms offered by tech giants has led to the implementation of data annotations with multiple functions, such as recognition facial recognition, object recognition and landmark detection.

  • Increasing integration of digital image processing and mobile computing platforms into various digital shopping and document verification applications propels the market growth

Market dynamics

Market factors

  • Growing need to make text/image more interactive and engaging

  • Rapid penetration of AI and machine learning

  • Increase in R&D expenditure for the development of autonomous vehicles

Market restriction

  • Lack of skilled labor

  • High costs associated with manual labeling of complex images

Main topics covered:

Chapter 1 Methodology and Scope

Chapter 2 Executive Summary

Chapter 3 Market Variables, Trends and Scope

Chapter 4 Data Collection and Labeling Market: Data Type Estimates and Trend Analysis

Chapter 5 Data Collection and Labeling Market: Vertical Estimates and Trend Analysis

Chapter 6 Data Collection and Labeling Market: Regional Estimates and Trend Analysis

Chapter 7 Competitive Landscape

Companies cited

  • app limited

  • Reality AI

  • Global Localization Inc.

  • Global Technology Solutions

  • alegion

  • Labelbox, Inc.

  • Dobility, Inc.

  • AI Scale, Inc.

  • Trilldata Technologies Pvt. ltd.

  • Play Inc.

For more information about this report visit https://www.researchandmarkets.com/r/o7g7mq

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