Data Analytics (DA) is the science and collection of techniques used to examine and analyze data sets in order to make observations and draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data Analytics consists of descriptive analytics to show patterns in the data, predictive analytics used to make forecasts from existing data, and prescriptive analytics that shows best solutions for decision making. Data analytics technologies and techniques are widely used in business, government, and military applications, to enable individuals and organizations to make more accurate decisions, and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.
The importance of Data Analytics originally arose from the availability of vast amounts of data, and the need to analyze this data in a rapid, complete, and correct manner, to support decision making. The combined needs have driven the rapid development of techniques, models, and technologies, that have made Data Analytics mandatory for the support of decisions in business, government, and military applications.
Data Analytics is a relatively new combination of methods, tools, and technologies, even though some of these concepts are established and have been widely used. In recent times, Data Analytics has seen massive growth as a field in its own right because of combined developments in associated areas of large-scale data warehousing, communications technologies, cloud computing, and mobile computing.