Data assimilation is a process used in various fields, such as meteorology and oceanography, to improve predictions by combining observational data with mathematical models. It helps to create a more accurate representation of the current state of a system, allowing for better forecasts and analyses. The technique involves using algorithms to integrate real-time data, like satellite observations or weather station readings, into existing models. This integration helps to correct errors in the models and provides a clearer picture of complex systems, ultimately enhancing decision-making and planning in areas like climate science and disaster management.