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Predictive data analysis

Predictive analytics tries to predict future situations and scenarios. To do this, algorithms evaluate historical and current data. The goal is, for example, to use personnel and other resources as efficiently as possible. In the future, predictive intelligence will increasingly be used in relation to human behaviour. 

Based on analysed data, the software is supposed to predict which step certain users will take next. This prepares automated decision-making. Predictive analytics goes one step further and provides recommendations for action in addition to the probability of occurrence for certain scenarios. This enables automated decision-making. For this purpose, extensive data from different sources is analysed with the help of algorithms. Artificial intelligence, simulations, statistical methods and probability calculations are used. 

Significance for optics: 

In the course of advancing digitalisation, predictive analytics also enables a more precise allocation of resources and personnel in the optical sector. The algorithm-based evaluations enable companies to optimise their material planning, for example, by using predictive analytics to develop scenarios in which excess material or delivery bottlenecks can be avoided on the basis of the available data. For opticians, data can give hints about customer´s vision development and respective treatment. 

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