Analyzing numerical data validating identification numbers
Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decision-making.
Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains.
In mathematical terms, Y (sales) is a function of X (advertising).
It may be described as Y = a X b error, where the model is designed such that a and b minimize the error when the model predicts Y for a given range of values of X.
Data are collected and analyzed to answer questions, test hypotheses or disprove theories.
Statistician John Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." The CRISP framework used in data mining has similar steps.
Once processed and organised, the data may be incomplete, contain duplicates, or contain errors.
The process of exploration may result in additional data cleaning or additional requests for data, so these activities may be iterative in nature.
In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA).
EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses.
Analysts may attempt to build models that are descriptive of the data to simplify analysis and communicate results.
A data product is a computer application that takes data inputs and generates outputs, feeding them back into the environment. An example is an application that analyzes data about customer purchasing history and recommends other purchases the customer might enjoy.