the data has been collected in the first place?

Now, let me start that, sort of the answer to that again.

If you think about why, why do you want to check data quality before you plunge into doing a modeling and analysis? Well, the first thing is, If there is anything wrong in the data, you want to find that out as soon as possible in case it would invalidate all your modeling.

In case you find out, oh, actually, I've got data for this, but I need to get different data for that.

Even if the data itself is, let's say, suitably correct and there isn't too much that's missing, you may have assumptions about the data.

And so another aspect of why you check data quality is to make sure that your assumptions about the data are the same as the data itself.

The what is then what are the checks that you do? And there are actually quite a lot of checks that you should consider doing.

Is there a data quality failure story you can share with it without breaking NDAs or commercial agreements that genuinely surprised you where the data looked fine, but when you started looking more closely, you discovered it wasn't.