One use case is in theoretical physics, where expressions that take up about a terabyte are generated when computing Feynman diagrams, but only in the intermediate stages. By the end of a two-month computation you get a result similar to equation 4.5 in this paper: https://arxiv.org/pdf/1707.01044
An exact answer is desired since the final result reveals some structure that can be studied, and because it is very hard to get a numerical result due to the occurrence of spurious poles. For example, evaluating
(1-x)/x - 1/x
numerically is challenging around x=0 even though symbolically it can be made regular.
Evaluating the expression naively near zero you're going to get wild numerical errors, but if you do the symbolic manipulation you're going to notice that it's just equal to -1.
Edit: e.g. consider this interaction I just had with the python interpreter
An exact answer is desired since the final result reveals some structure that can be studied, and because it is very hard to get a numerical result due to the occurrence of spurious poles. For example, evaluating
(1-x)/x - 1/x
numerically is challenging around x=0 even though symbolically it can be made regular.