Normal-Log transformation of the data

I have the following dependent and independent variables for my linear regression model. Since they are all in different scales (some of the are % others continuous variables), I was suggested to take the log and normalize them before running the regression.

    Y    X2        X3 (%)       X1 (%)
Mean 2.9 24.6   0.009517    230.992248
std  2.3 32.2   0.077092    230.992248
Min  0   1      0           0
Max  8   539    1           1

I have the following Qs:

Why should I take the log and then normalize them - rather than using just one of the two data transformations?

Should I log and normalize also my Y variable?

How would interpret my coefficient at the end of the exercise? and how can I make them humanly intelligible for a business audience?

Any easy doc reference is very appreciated!