Suppose data set is expressed by the matrix $X \in\mathbb R^{n \times d}$
where $n =$ Number of samples and $d =$ dimension/features of each sample
Then what does $\operatorname{Cov}(X) \in\mathbb R^{d \times d}$ (Variance-Covariance matrix of $X$) represent. Does below interpretation would be right
Variance-Covariance matrix of $X$ represents covariance between every pair of dimension/feature for all samples.