You can use the covariance to understand the direction of the relationship between variables. Positive covariance values indicate that above average values of one variable are associated with above average values of the other variable and below average values are similarly associated. Negative covariance values indicate that above average values of one variable are associated with below average values of the other variable.
The correlation coefficient is a function of the covariance. The correlation coefficient is equal to the covariance divided by the product of the standard deviations of the variables. Therefore, a positive covariance always results in a positive correlation and a negative covariance always results in a negative correlation.