In general terms, the science of data is the extraction of knowledge of data sets1,2. It uses techniques and theories derived from several other broader fields of mathematics, mainly statistics, information theory and information technology, including signal processing, probabilistic models, automatic learning, Statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, prophetic analytics, uncertainty modeling, data storage, data compression and computing High performance. Methods that adapt to mass data are particularly interesting in the science of data, although discipline is generally not considered to be limited to this data.