Vision 2027 - The Future of Data Annotation Tools Market Transformations and Growth Opportunities

1. Data Annotation Tools Market to 2027 Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others )

2. Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others ) The data annotation tools Market was valued at US$ 695.5 million in 2017 and is projected to reach US$ 6450.0 million by 2027; it is expected to grow at a CAGR of 32.54% from 2020 to 2027.

3. Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others ) The process of data annotation includes labeling of data which makes it usable for machine learning. Data annotation tools are an important tool 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, or any other language), 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 data is huge outsourcing it to companies like Precise BPO Solution who can handle millions of annotations in a week could save time. The threat of coronavirus resulting the disease COVID-19 is expected to have disruptive impact on the economy, globally. It has disrupted the global supply of goods and services resulting the companies to fulfill the orders. It has resulted to reduced labor on supply side and slow down in the demand for products and services other side. Due to the shutdown of businesses and the fall in the demand of data annotation tools in the first quarter of 2020, the market is negatively impacted. Moreover, due to the falling GDP, the market will have negative impact on the growth rate of data annotation tools market. However, it is expected that the economy will regain its momentum soon; the market for data annotation tools will witness a significant demand.

4. Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others ) Machine learning and artificial intelligence are among fastest-growing technologies that are introducing incredible innovations and offering various advantages to several industries globally. Data annotation includes the process of labeling/tagging video, images, text, and speech. For machine learning, precisely labeled datasets are needed, so that machines can easily and clearly understand the input patterns. When the dataset is precisely labeled, an accurate output can be expected. Chatbots and virtual assistant devices solve user queries and can give information about a specific product, services, weather conditions, as well as latest news updates of a particular city or country.

5. Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others ) In semi-automatic/semi-supervised annotation, human annotators use computer algorithms to produce annotations, providing suggested tags to users. They allow the users to provide the system with feedback on suggested image/text tags. The user-generated feedback can then be used to create accurate keyword suggestions. Semi-automating the labeling process eliminates the labor costs and also reduces the time taken to get a model trained and into production. It is also used to monitor model assessments and enhance the accuracy of deployed machine learning systems. The ease of use and improved speed of the entire annotation task favor the growth of this segment in the data annotation tools market during the forecast period. Data Annotation Tools Market Companies Profiles Appen Limited, CloudFactory Limited, Cogito, Deep Systems, Google LLC, Labelbox, Inc, LIGHTTAG, Tagtog Sp. z o.o., PLAYMENT INC., SCALE AI, INC.

6. Global Analysis and Forecasts by Type ( Text, Image, Others ); Annotation Type ( Manual, Semi-Supervised, Automatic ); End-user ( Automotive, Government, Healthcare, Financial Services, Retail, IT and Telecom, Others ) Thank You Email :sales@theinsightpartners.com Phone : +1-646-491-9876