There are two reasons why it is important to find relationships between variables in the data:
Finding which features are potentially important can be deemed essential, since finding ones that have a strong relationship with the target variable will aid in the feature selection process.
Finding relationships between different features themselves can be useful, since variables in the dataset are usually never completely independent of every other variable and this can affect our modeling in a number of ways.
Now, there are a number of ways we can visualize these relationships, and this really depends on the types of variable we are trying to find the relationship between, and how many we are considering as part of the equation or comparison.
