Why aren't languages like C, C++ used for data analytics instead of R, Python?
Yes, you're correct -- it's that C and C++ are harder to use and are more burdened with boilerplate code that obfuscates your model building logic. When you build models, you have to iterate rapidly and frequently, often throwing away a lot of your code. Having to write boilerplate code each time substantially slows you down over the long run.  Using R's caret package or Python's scikit-learn library, I can train a model in just 5-10 lines of code. 

Ecosystem also plays a big role. For example, Ruby is easy to use, but the community has never really seen a need for machine learning libraries to the extent that Python's community has. R is more widely used than Python (for stats and machine learning only) because of the strength of its ecosystem and its long history catering to that need. 

It's worth pointing out that most of these R and Python libraries are written in low-level languages like C or Fortran for their speed. For example, I believe Google's TensorFlow is built with C, but to make things easier for end users, its API is in Python.