Covering the essentials of business intelligence, explore the features & functions for an overview.
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Data exploration is the process of describing the main characteristics of a set of data. This is often the first step people take when performing data analysis. During this process, the analyst decides which questions the data is going to answer, what hypothesis it will likely support, and which variables have meaningful relationships. During the data exploration phase, analysts familiarize themselves with the data while seeking these answers.
The most common way analysts perform the data exploration step is through data visualization software. By having quick access to data and the ability to view relationships in a graphical way, users can easily see which variables have a significant relationship and should be analyzed further. For example, a user can use a BI tool to create a scatter plot comparing two variables. They can then replace one of the variables with another, then continue this process until they notice a correlation in the plot. They may then decide to pursue the relationship between those variables further, discovering if there is any information that could benefit their company.
There are two main steps in performing data exploration: univariate analysis and bivariate analysis.
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