The goal of the data visualization is to expose something new about the underlying patterns and relationships contained within the data. The visualization not only needs to look good but also meaningful in order to help organizations make better decisions. Visualization is an easy way to jump into a complex dataset (small or big) to describe and explore the data efficiently.
Many kinds of data visualizations are available such as bar chart, histogram, line chart, pie chart, heat maps, frequency Wordle (as shown in the following figure) and so on, for one variable, two variables, and many variables in one, two, or three dimensions.
Data visualization is an important part of our data analysis process because it is a fast and easy way to do an exploratory data analysis through summarizing their main characteristics with a visual graph.
The goals of exploratory data analysis are listed as follows:
Detection of data errors
Checking of assumptions
Finding hidden patterns (such as tendency)
Preliminary selection of appropriate models
Determining relationships between the variables
We will get into more detail about data visualization and exploratory data analysis in Chapter 3, Data Visualization.