Random Variable vs data vs random sample

I have a problem understanding the difference between random variable and random sample. I have read this thread, but still it is unclear. According to wiki random variable is a function that from a set of outcomes (events) to measurable values $\Omega$ -> $E$ where $E$ could be $\mathbb$ . And random sample is a possible outcome. So, in a lecture script I have these sentences which are confusing me:

let $D=\$ be a set of random variables.

Now I want to create a concrete example for myself to understand what $\$ could be. Let's take the sample of two dice where we want to compute the probability of the sum of the figures of dice we have thrown. So we construct a random variable $X$ which just adds the thrown number of the dice: $$X:\Omega\to\mathbb$$ $$X(\text_1,\text_2) = \text_1 + \text_2 $$ Where dice are uniformly distributed in $ \ < 1,\cdots,6 \>$ . And as far I know, if I throw two diсe, I have concrete values which are my random samples. Now my concrete question is: what could be in this specific example a set of random variables $D=\$ ? And what are then the concrete random samples? UPDATE:
After reading the comments and replies, I want to underline, that I have a specific question and I would appreciate if someone could answer it explicitly: In the above example please give me a concrete $D = $ as a set of random variables. I want to see how a set of random variables $D = $ (more than 2 random variables) would look like in this example.