Big data analytics is the process of collecting, storing, and analyzing large and complex datasets to uncover insights and trends from varied, high-volume, high-velocity datasets. These datasets are characterized by the 3Vs: volume, variety, and velocity. It is often too large in volume to be stored and processed on a single computer or server and may come in a variety of different formats and types such as from structured (database tables, Excel sheets) to semi-structured (XML files, webpages) to unstructured (images, audio files). It is also generated at a high velocity, meaning that it is collected and generated at a rapid rate, making it difficult to process in real time using traditional systems. 

Big data analytics involves using advanced technologies and algorithms to extract valuable information from large volumes of data, and to use that information to make better-informed business decisions. One of the key tools used in big data analytics is Hadoop, a framework that allows for the distributed processing of large datasets across clusters of computers. Image Source