The digitization in agriculture is increasingly being adopted with huge economic and ecological benefits. Weather forecasts, satellite images, biophysical parameters, soil analysis measures along with images from field robots and drones are just some of the various types of data that are correlated in order to optimize production processes, growth conditions and mitigate risks. Data science has done huge leaps providing a plethora of libraries and frameworks to facilitate scientists in their complicated tasks of developing algorithms that predict future events and propose adapted actions. Nevertheless, to effectively pass into production, experts have to consider different sources and types of data, cope with the limitations of the underlying hardware compute infrastructure, take into account the specificities of the algorithms while dealing with data collection temporality, time criticality and data privacy. Ryax is a software addressing these exact issues with a platform that allows data scientists to create, deploy and manage data analytics workflows simply, by abstracting the complex data engineering plumbing.
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