Contemporary applications of big data in science.

Genomics: The application of big data tools to analyse and comprehend genetic data, resulting in new insights into illness diagnosis and treatment.

The utilisation of enormous volumes of data from weather and climate sensors to enhance forecasts and knowledge of the Earth's climate system.

Astrophysics: The study of the cosmos using big data tools to analyse and understand massive volumes of data provided by telescopes and other sensors.

Materials science is the study of the characteristics and behaviour of materials using big data, including the development of novel materials with enhanced properties.

Neuroscience: The study of brain imaging and other data using big data to better understand the workings of the brain and create innovative therapies for neurological diseases.

Drug discovery is the process of identifying possible new medications and better understanding the mechanisms of current drugs using big data and machine learning algorithms.

Environmental monitoring is the use of large data from environmental sensors to monitor and comprehend changes in the natural world, such as ecosystem changes and the influence of human activity.

These are just a few instances of how big data is now being used in science. Big data is assisting scientists in making new discoveries and better understanding complicated systems and processes.