I think that this is something to do when you have a "good" data set in hand - when you've filtered and checked and wrangled the data into something approximati

I think that this is something to do when you have a "good" data set in hand - when you've filtered and checked and wrangled the data into something approximating a training table. Or if the data is set to you after that process or the collection process has produced good clean data (for example survey results). Until then I don't think that PCA really tells you what you need to know - which is "is this data set what I think it is " and "is the information that I need to extract actually in here"?