# Data Science and Analytics

__Data Science:__

Data Science is also known as ‘**data-driven science**‘. It is an interdisciplinary field of scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, it’s similar to data mining. Data Science is one of the recent fields combining big data, unstructured data and a combination of statistics and analytics and business intelligence. It is a new field that has emerged within the field of data management providing an understanding of the correlation between structured and unstructured data.

Data Science is the discipline of using quantitative methods from statistics and mathematics along with technology to develop algorithms designed to discover patterns, predict outcomes and find optimal solutions to complex problems. Nowadays, data scientists are in great demand as they can transform unstructured data into actionable insights, helpful for businesses.

Data Science is blossoming as a “concept to unify statistics, data analysis and their related methods” to “understand and analyze actual phenomena” with big data. In its extended canvas, data science employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data lakes, data mining and data warehouse, databases and visualization.

__Data Analytics:__

Data analytics are general terms used to describe the field and a comprehensive collection of associated methods. All these terms tend to be used for the application of analytics methods to data that large organizations generate.

Data analysts collect, process and perform statistical analyses of data. Their skills may not be as advanced as data scientists, but their goals are the same – to discover how data can be used to answer questions and solve problems.