The global data annotation tools market was valued at US$ 695.5 million in 2019 and is projected to reach US$ 6,450.0 million by 2027; it is expected to grow at a CAGR of 32.54% from 2020 to 2027.
The process of data annotation includes labeling of data which makes it usable for machine learning. Data annotation tools are important for data scientists as they make use of the labeled data with machine learning algorithms. Data can be in any form, such as images (from cars, phones, or medical instruments), text (in English, Spanish, Chinese, and among others), audio, and video. There are different types of annotation techniques like polygon annotation, semantic segmentation, bounding box annotation, landmark annotation, polylines annotation, and 3D point cloud annotation. In house teams can label the data if it is a small set, but this can be time consuming. When large amount of data is to be annotated, it is outsourced to companies like Precise BPO Solution, who can handle millions of annotations in a week and it significantly saves time. Further, the increasing investments by various market players in data annotation techniques in order to offer high quality labeled data are expected to play a significant role in the growth of the market.
The applications of data annotation are growing strongly across the globe. Face detection and recognition is one of the major applications of data annotation. Countries across the globe are implementing various facial technologies to create social status and award penalties for public menace to its citizens. For instance, China has installed 200 million surveillance cameras, one camera for every seven of its citizens. It plans to install about 400 million new cameras by 2021 in the country, for security and traffic control purposes.
The market for data annotation tools has been segmented into type, annotation type, end user, and geography. Based on type, the data annotation tools market has been segmented into text, image, and others. Based on annotation type, the data annotation tools market has been segmented into manual, semi-supervised, and automatic. Based on end user, the data annotation tools market has been segmented into automotive, government, healthcare, financial services, retail, IT & telecom, and others. Geographically, the data annotation tools market is segmented into five regions: North America, Europe, APAC, MEA, and South America.
Appen Limited, CloudFactory Limited, Cogito, Deep Systems, Google LLC, Labelbox, Inc, LIGHTTAG, Tagtog Sp. z o.o., PLAYMENT INC., and SCALE AI, INC. are some of the well-established market players present in the global data annotation tools market.
The overall size of global data annotation tools market has been derived using primary and secondary sources. The research process begins with extensive secondary research using internal and external sources to obtain qualitative and quantitative information related to the global data annotation tools market. It also provides an overview and forecast for the data annotation tools market based on all the segmentations provided for the global regions. Additionally, primary interviews were conducted with industry participants and commentators to validate data and analysis. The participants who take part in such a process include industry expert such as VPs, business development managers, market intelligence managers, and national sales managers, and external consultants such as valuation experts, research analysts, and key opinion leaders specialized in data annotation tools.
Reasons to Buy:
The process of data annotation includes labeling of data which makes it usable for machine learning. Data annotation tools are important for data scientists as they make use of the labeled data with machine learning algorithms. Data can be in any form, such as images (from cars, phones, or medical instruments), text (in English, Spanish, Chinese, and among others), audio, and video. There are different types of annotation techniques like polygon annotation, semantic segmentation, bounding box annotation, landmark annotation, polylines annotation, and 3D point cloud annotation. In house teams can label the data if it is a small set, but this can be time consuming. When large amount of data is to be annotated, it is outsourced to companies like Precise BPO Solution, who can handle millions of annotations in a week and it significantly saves time. Further, the increasing investments by various market players in data annotation techniques in order to offer high quality labeled data are expected to play a significant role in the growth of the market.
The applications of data annotation are growing strongly across the globe. Face detection and recognition is one of the major applications of data annotation. Countries across the globe are implementing various facial technologies to create social status and award penalties for public menace to its citizens. For instance, China has installed 200 million surveillance cameras, one camera for every seven of its citizens. It plans to install about 400 million new cameras by 2021 in the country, for security and traffic control purposes.
The market for data annotation tools has been segmented into type, annotation type, end user, and geography. Based on type, the data annotation tools market has been segmented into text, image, and others. Based on annotation type, the data annotation tools market has been segmented into manual, semi-supervised, and automatic. Based on end user, the data annotation tools market has been segmented into automotive, government, healthcare, financial services, retail, IT & telecom, and others. Geographically, the data annotation tools market is segmented into five regions: North America, Europe, APAC, MEA, and South America.
Appen Limited, CloudFactory Limited, Cogito, Deep Systems, Google LLC, Labelbox, Inc, LIGHTTAG, Tagtog Sp. z o.o., PLAYMENT INC., and SCALE AI, INC. are some of the well-established market players present in the global data annotation tools market.
The overall size of global data annotation tools market has been derived using primary and secondary sources. The research process begins with extensive secondary research using internal and external sources to obtain qualitative and quantitative information related to the global data annotation tools market. It also provides an overview and forecast for the data annotation tools market based on all the segmentations provided for the global regions. Additionally, primary interviews were conducted with industry participants and commentators to validate data and analysis. The participants who take part in such a process include industry expert such as VPs, business development managers, market intelligence managers, and national sales managers, and external consultants such as valuation experts, research analysts, and key opinion leaders specialized in data annotation tools.
Reasons to Buy:
- Highlights key business priorities in order to assist companies to realign their business strategies.
- The key findings and recommendations highlight crucial progressive industry trends in the data annotation tools market, thereby allowing players to develop effective long-term strategies.
- Develop/modify business expansion plans by using substantial growth offering developed and emerging markets.
- Scrutinize in-depth global market trends and outlook coupled with the factors driving the market, as well as those hindering it.
- Enhance the decision-making process by understanding the strategies that underpin commercial interest with respect to components, aircraft type, and end-users.
Table of Contents
1. Introduction
3. Research Methodology
4. Data Annotation Tools Market Landscape
5. Data Annotation Tools Market - Key Industry Dynamics
6. Data Annotation Tools Market - Global Market Analysis
7. Data Annotation Tools Market Analysis - By Type
8. Data Annotation Tools Market Analysis - By Annotation Type
9. Data Annotation Tools Market Analysis - By End User
10. Data Annotation Tools Market - Geographic Analysis
11. Industry Landscape
12. COMPANY PROFILES
13. Appendix
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Cogito
- Google LLC.
- Deep Systems
- Appen Limited
- Labelbox, Inc
- LightTag
- PLAYMENT INC
- Scale AI, Inc.
- Tagtog Sp. z o.o.
- CloudFactory Limited
