Data analysis is the process of inspecting and modeling data in order to discover useful information. Data analysis has a myriad of different techniques, as well as applications throughout the various disciplines, from business to science to the social sciences. The term analysis, in general, refers to breaking down information into separate components in order that it can be used to answer questions. The major divisions of data analysis are qualitative analysis, which looks for patterns, or quantitative analysis, which focuses on hard numbers.
The first stage is data analysis is data collection. Inputs must be gathered, and the type of collection often depends upon the discipline in which one is conducting research. Raw data can consist of interviews, scientific observations, or mathematical calculations. Data can be collected by the researcher, or come from any number of automatic sources, such as environmental sensors. Once the data is collected, it must be processed. Often, simple organization of data into rows, columns or charts greatly facilitates analysis.
Once the data is collected, processed, and organized, it must be cleaned. This removes duplicate entries or errors. At this point, the data can be analyzed. Data analysis is a valuable tool in research, allowing for the synthesis of large amounts of information that no only answer research questions, but provide clear insight into the problem at hand for readers.