Correlation measures the degree of co-movement between pairs of variables in your dataset and is scaled between -1.0 to 1.0. Two variables are considered to have a perfect positive correlation at 1.0, moving together in the same direction, all the time. Variables with 0.0 correlation are considered uncorrelated, co-moving in a random pattern. A correlation matrix allows a user to view co-movement of all the possible pairs of data in a single visual.