Purpose of converting continuous data to categorical data
Your intuition is generally correct - in many cases, premature discretization of continuous variables is undesirable. Doing so throws away potentially meaningful data, and the result can be highly dependent on exactly how you bucket the continuous variables, which is usually done rather arbitrarily. Bucketing people by age decade, for example, implies that there is more similarity between a 50-year-old and a 59-year-old than there is between a 59-year-old and a 60-year-old. There can be some advantages in statistical power to doing this, but if your binning doesn't reflect natural cutpoints in the data, you may just be throwing away valuable information.

You can find a very similar question here:

https://stats.stackexchange.com/questions/68834/what-is-the-benefit-of-breaking-up-a-continuous-predictor-variable?noredirect=1&amp;lq=1