If you have the basics (identifying outliers, missing values, weighting, coding) depending on the topic there's a lot more in the plain academic literature to be found. For example in survey research (which is a topic where many things can go wrong, and prone to many sources of bias) there are a lot of good articles to be found.
When preparing for regular crossectional regression, things may be less complex.
Problem there may for example that you remove too many 'outliers' and thus artificially fitting your model well.
I thus also recommend you besides learning good techniques, also keep common sense in mind. Make sure you apply the techniques rightfully and not blindly. As for the software discussion in the other answers. I think SPSS is not bad for data preparation (I also heard good things about SAS) depending on your dataset size. The drop down menus are very intuitive.
But as a direct answer to your question, academic literature may or may not be a very good source for your data preparation depending on the topic and analysis.