The “Data Collection And Labeling Market Size, Share & Trends Analysis Report By Data Type (Audio, Image/ Video, Text), By Vertical (IT, Automotive, Government, Healthcare, BFSI), By Region, And Segment Forecasts, 2023 – 2030” report has been added to ResearchAndMarkets.com’s offering.
DUBLIN, Sept. 18, 2023 /PRNewswire/ — The global data collection and labeling market is on a trajectory for significant growth, with an expected size of USD 17.10 billion by 2030, expanding at a remarkable CAGR of 28.9% from 2023 to 2030.
Data collection and labeling involve the collection of datasets from diverse sources and categorizing them based on their nature, including data type and features. This process, when combined with AI technology, has unlocked substantial growth opportunities across various industries, including gaming, social networking, and e-commerce.
For instance, social media giants like Twitter and Facebook have harnessed image-processing technology to enhance audience engagement. Companies utilize data labeling platforms to identify raw data for machine learning models, encompassing various data types such as text, movies, audio, and more. Notably, Heartex, Inc., a data labeling platform provider, recently secured USD 25 million in a Series A fundraising round in May 2022. These funds are earmarked for the development of an AI-driven open-source data labeling platform, aimed at streamlining labeling workflows for diverse AI use cases, incorporating features for reporting, data quality control, and analytics.
The proliferation of digital capturing devices, particularly smartphone cameras, has led to an explosion in digital content in the form of images and videos. This abundance of visual and digital data is shared across numerous applications, websites, social networks, and digital channels. Many businesses leverage this online content to deliver innovative and superior customer services through data annotation. Scale AI, Inc., a U.S.-based tech start-up, provides data labeling services to autonomous driving companies like Waymo LLC, Lyft, Inc., Zoox, and Toyota Research Institute, showcasing the significance of data annotation in cutting-edge technologies.
However, data cleaning remains a significant challenge in the data labeling process. Additionally, the complexity, time, and cost involved in developing machine learning models may require substantial resources for accurate results. Consequently, many companies are strategically expanding their presence in artificial intelligence-based data gathering. For example, in July 2020, Microsoft acquired Orions Digital Systems, Inc., a U.S.-based data management solutions provider, to enhance its Dynamics 365 Connected Store capabilities. This acquisition is expected to leverage computer vision and IoT sensors to help retailers gain deeper insights into customer behavior and manage physical spaces more efficiently.
Key Highlights of the Data Collection and Labeling Market:
- Automated image organization through cloud-based applications and telecom companies has significantly improved user experiences and attracted customer attention.
- Facial recognition technology is being increasingly deployed in public spaces and events due to benefits like enhanced security and automation.
- Tech giants offering large-scale cloud-hosted AI and machine learning platforms have driven the adoption of data annotation for various functions, including facial recognition, object recognition, and landmark detection.
- The integration of digital image processing and mobile computing platforms in digital shopping and document verification applications is fueling market growth.
Key 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.
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
3.6 Penetration & Key Opportunities Mapping
3.7 Data Collection and Labeling – PEST Analysis
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/pk0izq
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