Data are used for the development of automated systems and customised technological products, which usually call for data sets with specific requirements. Among these are AI-powered personal assistants, cybersecurity systems and smart security models associated with computer vision.
In this field there are many repetitive and procedural tasks that have been automated to save time and money. Data sets can be used for the development of robo-advisors to monitor finances and provide targeted advice, fraud detection and insurance risk calculation, credit scoring and investment analysis.
Through the use of algorithms, it’s possible to develop systems of prediction, but also inventory and optimisation systems for production processes. Data can be used to develop automatic production systems, optimise the industrial production line, implement voice and facial recognition models for an end product.
In this industry, data can be used to automatically manage production processes and to develop systems for facial and voice recognition, adaptive cruise control and other settings that can be implemented in vehicles.
Training data can help to improve the customer travel experience and quicken some processes. For example, data can be used for the development of chatbots and virtual assistants capable of helping tourists or for implementing facial recognition systems for facilities.
In this field, training data can be used for the development of automatic systems for checking patients’ health and for research and accurate diagnosis of certain illnesses. They can help the automatic management of prevention and of remote medical check-ups and to improve remote diagnostic and analytic systems.
Data sets can be used for the development of customer care services and for the improvement of customer experience. Therefore, training data can be used for the creation of customised chatbots and digital assistants, the development of sentiment analysis models to analyse feedback and manage recommendations for personalised purchases.
Data can be used for the development of fact-checking systems and the management of conversations on social media and websites. In particular, training data can be used for automatically managing content, recording feedback related to user content and developing optimisation systems for online research.