how do know if your dataset is good before using ML algorithms?

hi everyone

I need to know what test or node I must use to ensure

that my data are balanced (I don’t mean it has missing value or needs normalizing) I mean it’s a real dataset that does not have random value or no sense in it when I use ML algorithms on it. The result of machine learning will be good

to make decisions on it, I used to use the heart dataset (to apply like videos I watch) but I figured out it was a bad dataset because all ML algorithms gave me bad results. Still, I can’t test all algorithms every time.

I would appreciate any information from your education or experience that can help me.

thanks all