Annotating data is a way to organize unstructured data into structured information, used in machine learning applications. It describes the images, texts, and videos available in the form of labels. Machine learning algorithms benefit from data annotation tools, which enable them to label input data so that machine learning algorithms can understand input clearly and provide accurate results. The annotation tools enhance the end-user experience and improve the accuracy of output. As artificial intelligence is used more widely in various sectors, data annotation tools will become more necessary in image and voice recognition, where labelled data will benefit machine learning.
Market Dynamics for Data Annotation:
An increasing number of automotive, healthcare, banking and finance industries are increasingly utilizing AI, as are new technologies and the adoption of advanced technologies. Data annotation tools assist automotive manufacturers in developing smart applications such as natural language processing (NLP) and voice recognition. Several advanced technologies, such as the Internet of Things (IoT), robotics, machine learning, artificial intelligence, and advanced predictive analytics, generate huge volumes of data. Therefore, technology changes require data efficiency for crafting new business innovations, economies, and infrastructure that continuously boost the market growth.
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Data annotation tools, which aim to improve the e-commerce sector in the retail sector, are expected to drive the market’s growth during the forecast period. For example, Walmart Labs acquired a start-up in India called Dataturks in 2019, which uses machine learning to process text and images. With this acquisition, Walmart was able to innovate on the merchandising platform and in quality. Furthermore, various companies invest funds into developing data annotation to gain an advantage over their competitors. For example, Hive, a data labelling service provider, raised USD 30 million in venture capital funds last year, including money from PayPal founder Peter Theil’s founder’s funds.
Covid-19 Impact on Data Annotation Market:
Due to the global pandemic of the Coronavirus, hospitals have had no choice but to deploy artificial intelligence and machine learning methods to curb the spread of a potentially deadly infection. However, inaccurate data labels due to poor quality content and a lack of skilled workers can hinder the growth of the global market for data annotations. Moreover, a manual annotation may involve errors in labelling on data, adding to the overall cost; moreover, with improved algorithms and tools for annotation, the need to rely on a manual annotation will decrease, and the cost of the tools will decrease in the future.
Aims of the report
An analysis of the market for data annotations based on annotation type, data type, and the application appears in the report.
The annotation type segment consists of the following sub-segments:
- Manual Annotation
- Automated Annotation
The data type segment consists of the following sub-segments:
- Text
- Images
- Video
- Audio
The application segment consists of the following sub-segments:
- Automotive
- Healthcare
- Agriculture
- IT & Telecom
- Retail
- BSFI
- Government
- Others
Regional Outlook for the Data Annotation Market
Based on geography, the data annotation market is divided into Asia Pacific, Europe, Latin America, North America, and Middle East & Africa (MEA). In 2019, North America was likely to hold the largest global data annotation market share. As a result of various industries’ rapid geographical and product expansion, they have gained a competitive edge. An increasing focus on image annotation in various industries, including the automotive and retail sectors, is one of the key factors driving the global data annotation market. The market has been boosting due to the increasing demand for smart products and high disposable income in the region.
The predictions are that the Asia Pacific will experience the highest annual growth rate during the forecast period. Data annotation tools are very attractive to developing economies in the Asia Pacific, particularly in the banking and financial services and healthcare sectors. The Asia Pacific region has seen substantial growth in the healthcare market over the next few years due to a wide range of advanced technologies and innovative healthcare programs. As a result, Malaysia, Indonesia, and India are experiencing increasing amounts of digitalization. Governments are promoting the adoption of new technologies in every vertical, so big data analysis becomes necessary and results in demand for these tools, which then drives the market in the region.
Competitors in the Global Data Annotation Market include –
Globally, the top manufacturers of data annotations are – Amazon Mechanical Turk, Inc., Appen Limited, Edgecase, and Hive, Playment Inc.
In addition, Annotate.com, CloudApp, Cogito Tech LLC, Labelbox, Inc., and Clickworker GmbH are other data annotation manufacturers.
- In August 2018, Toyota invested $500 million into Uber’s Advanced Technology Group (ATG), an autonomous taxi program that focuses on self-driving vehicles. Through this fund, ATG acquired Mighty AI, a data-labeling company specializing in annotating autonomous vehicle data.
- In December 2018, Playment and Scale AI partnered to develop a deep learning tool for Ouster to label LiDAR data quickly and accurately rapidly.
- In 2018, BMW Group invested a considerable portion of its revenue into its R&D of image annotation for products relating to autonomous vehicles.
An analysis of the global data annotation market appears in the report, which includes an overview of the market dynamics, business models, segmentation/regional analysis, and respective market shares and strategies adopted by the major players. The report includes a comprehensive analysis of global market factors with market statistics, showing regionally and segmentally breakouts of market share/growth. The report’s study will outlook one of the most exhaustive market analyses, capturing all the data annotation industry aspects.
Comprehensive Data Annotation Market Analysis includes:
- Market Size of 10 years
- Supply & Demand Analysis
- Market Segmentation & Regional Analysis
- Pricing Analysis
- Developed & Emerging Economies Analysis
- Market and Forecast Factor Analysis
- Product Life Cycle Analysis
- Porter’s Five Forces & Value Chain Analysis
- PEST Analysis
- Patent Analysis
- Market Opportunities, Risks, & Trends
- Regulatory Landscape
- Competition Landscape
- 15+ Company Profiles
- Conclusion & Recommendation
Market Regional Overview of Data Annotation Includes:
- South America
- North America
- Asia Pacific
- Europe
- The Middle East & Africa
Target Audience of Data Annotation Market
- Data annotation service providers
- Research institutions and universities
- Data annotation device manufactures
- Government authorities, associations, and organizations
- Tier 1 component suppliers
- Trade publications and magazines
- Independent Aftermarket players
Table of Content
Chapter 1: Global Data Annotation Industry Overview
Chapter 3: Market Dynamics
Chapter 4: Top Company Profiles
Chapter 5: Global Data Annotation market Competition, by Players
Chapter 6: Global Market Size by Regions
Chapter 7: Global Market Segment by Application
Chapter 8: Global Data Annotation Industry Segment by Type
Chapter 9: Market Chain, Sourcing Strategy, and Downstream Buyers
Chapter 10: Strategies and key policies by Distributors/Suppliers/Traders
Chapter 11: Key Marketing Strategy Analysis, by Market Vendors
Chapter 12: Market Effect Factors Analysis
Chapter 13: Global Data Annotation market Size Forecast (2023-2032).
Continue….
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(A) The research provides valuable insights for top administration, policymakers, professionals, product advancements, sales managers, and stakeholders in the market. It helps them make informed decisions and strategize effectively.
(B) The report offers comprehensive analysis of Data Annotation market revenues on a global, regional, and country level, projecting trends until 2032. This data allows companies to assess their market share, identify growth opportunities, and explore new markets.
(C) The research includes segmentation of the Data Annotation market based on types, applications, technologies, and end-uses. This segmentation enables leaders to plan their products and allocate resources based on the expected growth rates of each segment.
(D) Analysis of the Data Annotation market benefits investors by providing insights into market scope, position, key drivers, challenges, restraints, expansion opportunities, and potential threats. This information helps them make informed investment decisions.
(E) The report offers a detailed analysis of competitors, their key strategies, and market positioning. This knowledge allows businesses to better understand the competition and plan their own strategies accordingly.
(F) The study helps evaluate Data Annotation business predictions by region, key countries, and top companies, providing valuable information for investment planning and decision-making.
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