Calculating smoothed derivative of a signal by using difference with larger step=convolving with rectangular window
This is a hard question to handle generally. Smoothing with a rectangular window is used all the time (often called a "moving average"), so that's not necessarily a problem. I'm not sure what ringing you're referring to, perhaps the sidelobes of the rectangular window's frequency response. 

Differentiation is inherently a highpass operation; the ideal continuous-time differentiator has a transfer function of:

$$
H(s) = s
$$

So that its magnitude response is:

$$
|H(j\omega)| = \omega
$$

The gain of a differentiator therefore increases monotonically with frequency. If your signal contains high-frequency noise, then it could be amplified by applying a differentiator. To combat this, two approaches are apparent:


Design a more sophisticated differentiator filter that has the desired linear magnitude response over the portion of the band that covers your signal of interest, then sharply attenuates higher frequencies. You could design such a filter using least-squares methods or the frequency-sampling method, for example.
Use a cascaded approach where you first suppress all of the high-frequency noise that you can using a lowpass filter, then follow with the differentiator. The frequency coverage of the differentiator need not be as tight since the lowpass filter will eliminate the out-of-band noise.


The methods should be roughly equivalent if you're using linear filters; you could think of the first single-filter approach as just a cascade of a differentiator and a lowpass filter. As you noted, the central-difference approach can be modeled in this way. It's hard for anyone to say that it's "bad" without any knowledge of your application. My main thought would be that it is "bad" if the smoothing operation tangibly attenuates your signal of interest, such that the derivative estimate is no longer useful. However, if the parameters of the signal are such that you can smooth the noise without noticeably distorting the signal (i.e. if the signal is well-oversampled), then it could be a win.