DUBLIN–(BUSINESS WIRE)–The “Global Data Collection And Labeling Market Size, Share & Trends Analysis Report by Data Type (Audio, Image/Video, Text), by Vertical (IT, Automotive, Healthcare), by Region, and Segment Forecasts, 2021-2028” report has been added to ResearchAndMarkets.com’s offering.
The global data collection and labeling market size is expected to reach USD 8.22 billion by 2028. The market is anticipated to expand at a CAGR of 25.6% from 2021 to 2028.
Companies Mentioned
Appen Limited Reality Ai Globalme Localization Inc. Global Technology Solutions Alegion Labelbox, Inc Dobility, Inc. Scale Ai, Inc. Trilldata Technologies Pvt Ltd Playment Inc. Data collection and labeling refer to the process of collecting datasets from online sources and other sources and labeling them based on their nature, data type, and feature. Data gathering and its annotation, combined with artificial intelligence (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 in the world of social networking, have benefited from the image processing technology in terms of audience engagement as they have created a more connected experience by encouraging users to share images and tag their friends.
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. A vast amount of visual and digital information is being captured and shared through several applications, websites, social networks, and other digital channels. Several businesses have leveraged this available online content to deliver smarter and better services to their customers, with the use of data annotation. For instance, Scale AI, Inc., the U.S.-based tech start-up, has provided 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 the development of machine learning models, many companies may not have the resources who can produce acceptable and accurate results. Therefore, several companies are taking strategic initiatives to expand their business in the field of 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 proliferate the use of computer vision and IoT sensors to help retailers better understand customer behavior and manage their physical spaces.
Data Collection And Labeling Market Report Highlights
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 users’ experience and drawn the customers’ attraction towards this technology Several benefits, such as better security and automation of identification, are the factors encouraging 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 applications such as digital shopping and document verification are propelling market growth Key Topics Covered:
Chapter 1 Methodology and Scope
Chapter 2 Executive Summary
Chapter 3 Market Variables, Trends & Scope
3.1 Market Segmentation & Scope
3.2 Data Collection And Labeling Size And Growth Prospects
3.3 Data Collection And Labeling – Value Chain Analysis
3.4 Data Collection And Labeling Market Dynamics
3.4.1 Market Drivers
3.4.1.1 Growing Need To Make Text/ Image More Interactive And Engaging
3.4.1.2 Rapid Penetration Of Ai And Machine Learning
3.4.1.3 Growing R&D Spending On The Development Of Self-Driving Vehicles
3.4.2 Market Restraint
3.4.2.1 Lack Of Skilled Labor
3.4.2.2 High Costs Associated With Manual Labeling Of Complex Images
3.5 Industry Analysis – Porter’s
3.5.1 Supplier Power
3.5.2 Buyer Power
3.5.3 Substitution Threat
3.5.4 Threat From New Entrant
3.5.5 Competitive Rivalry
3.6 Penetration & Key Opportunities Mapping
3.7 Data Collection And Labeling – Pest Analysis
3.7.1 Political
3.7.2 Economic
3.7.3 Social
3.7.4 Technological
Chapter 4 Data Collection And Labeling Market: Data Type Estimates & Trend Analysis
Chapter 5 Data Collection And Labeling Market: Vertical Estimates & Trend Analysis
Chapter 6 Data Collection And Labeling Market: Regional Estimates & Trend Analysis
Chapter 7 Competitive Landscape
For more information about this report visit https://www.researchandmarkets.com/r/kemnrd