Applying Shannon Entropy to data storage I know Shannon Entropy is defined for messages. When it's said the size of a file stored in a HDD is 1 MB, are we talking about the Shannon Entropy? If so, how do we extend the definition to static information (not flowing like messages)? If not, how come they have the same unit, i.e. bits?
No.  That is telling you the size of the file, i.e., that's a statement about its length, not its entropy.

Of course, the length gives an upper bound on the entropy, but it is not itself a value for the entropy.  The actual entropy could be smaller.

No, compressing the file does not tell you its entropy.  The length after compression is, on average, a reasonable upper bound for the entropy -- but the true entropy could be much smaller.

Beware that it only makes sense to talk about the entropy of a random process or the entropy of a distribution (e.g., the entropy of a process used to generate a file), not the entropy of a single file.  As an analogy, consider this old joke:



It doesn't make sense to say that "the number nine is random"; that's a property of the process used to generate the number, not the number itself.  You could get a 9 by rolling a ten-sided die (which is a random process), or you could get a 9 by writing the largest single-digit decimal number (that's not a random process).  Similarly, it doesn't make sense to ask what is the entropy of the number nine; that is not well-defined.  We can talk about the entropy of the random process that was used to generate it, though.

See a good textbook to learn more about the subject of entropy.