Mr. BHARAT B. DAREKAR
Department of Computer Science, KTHM College, Nashik, India.
Data science incorporates tools from multiple disciplines to gather a data set, process,
and derive insights from the data set, extract meaningful data from the set, and interpret it for
decision-making purposes. The disciplinary areas that make up the data science field include
mining, statistics, machine learning, analytics, programming, Big data analysis, data driven
theory, operations research, random processes, social network analysis, financial technology,
quantum computing, intelligent computing, cloud computing, optimization theory, decision-
making theory, computer simulation technology, health informatics, medical big data, and
health management. Data science combines aspects of different fields with the aid of
computation to interpret data for decision-making purposes.
Data mining applies algorithms to the complex data set to reveal patterns that are then
used to extract useful and relevant data from the set.
Machine learning is an artificial intelligence tool that processes mass quantities of data
that a human would be unable to process in a lifetime.
Data Analytics, the data analyst collects and processes the structured data from the
machine learning stage using algorithms. The analyst interprets, converts, and summarizes the
data into a cohesive language that the decision-making team can understand. Data science is
applied to practically all contexts and, as the data scientist's role evolves, the field will expand
to encompass data architecture, data engineering.