The biggest failure in graduate preparedness I found was that you learn the 'how' (eg: how to calculate a derivative or integral by hand or how to compute a determinant) without a deep understanding of the 'why', which means you don't truly Know those subjects. Even if such information is presented, it's typically not the focus of evaluation and is therefore not retained. Proof-based math coursework from first principles is the only way to really progress meaningfully in understanding these topics in a way that translates beyond just applying the mechanics you've learned. Real analysis is the first baby step most will take along that path, but the greater your depth/breadth of math knowledge the bigger your toolkit to solve problems in your chosen domain will be. It's hard to suggest subsequent steps without knowing your interest (eg: for OR, measure theory is critical but other topics might pay higher dividends for other fields).

> When you say calc-heavy, you are speaking about just cranking the wheel or number crunching?

There's a clear disconnect here: in my Swiss, CS undergrad calculus classes (1st and 2nd year), nothing was remotely as mechanical as those two choices. That (practice in hard math problem solving, not mechanical application of techniques) is probably what the grandparent is missing.