Data and information visualization: Difference between revisions

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=== Data analysis ===
[[Data analysis]] is the process of looking at and summarizing [[data]] with the intent to extract useful [[information]] and develop conclusions. Data analysis is closely related to [[data mining]], but data mining tends to focus on larger data sets, with less emphasis on making [[inference]], and often uses data that was originally collected for a different purpose. In [[statistics|statistical applications]], some people divide data analysis into [[descriptive statistics]], [[exploratory data analysis]] and [[confirmatory data analysis]], where the EDA focuses on discovering new features in the data, and CDA on confirming or falsifying existing hypotheses.
 
Types of data analysis are:-
* [[Exploratory data analysis]] (EDA): an approach to analyzing data for the purpose of formulating [[hypothesis|hypotheses]] worth testing, complementing the tools of conventional [[statistics]] for testing hypotheses. It was so named by [[John Tukey]].
* [[Qualitative data analysis]] (QDA) or [[qualitative research]] is the analysis of non-numerical data, for example words, photographs, observations, etc..
 
=== Data governance ===