Correlation between variables, in general, means that a change in one variable reflects on the other. However, it does not mean that the change in one variable is caused by the change in the correlated variable. For example, the selling price of a product is correlated to its manufacturing cost, but the price increase is not totally caused by it, since there are other factors such as transportation and inflation to take into account.
Not every variable or feature in a dataset is useful for the analysis that we are planning and, sometimes, many of them are redundant. Strong correlations between pairs of variables tell us which ones can be discarded and which ones are important to predict or explain the target variable.
Different correlation calculations can be performed in Excel and used to determine the relative importance of the input...
