In response to my post, Music in the Year 2009, AE Subject Matter Expert, Jason Pratt, sent me the following link: Free Download of Super Analyzer 2.1 from SourceForge I downloaded the ZIP file, unzipped it, and double-clicked on the extracted JAR file. I pointed the tool at my iTunes database: C:\Documents and Settings\Scott\My Documents\My Music\iTunes\iTunes Music Library.xml It provided some interesting data. For example, I most often listen to music at 11:00 AM: I have mostly been listening to songs from 2009. The blue line is the number of songs I have. The green line is the number of times I have listened to them. I like rock: Back in the days of coding in a computer language called C, we had a tool called lint. Lint analyzed your code and warned you of anything that was suspicious. In much the same spirit, SuperAnalyzer conducts a static analysis of your iTunes database and identifies any missing song attributes: I don't rate my songs. IMHO the point of having something like iTunes is to have your entire music collection on hand rather than play your same top 40 songs. Although I do play some songs more than others, I never rate them all, and then ask the system to play my favorites. So other than the missing ratings, I should not have any missing data. Based on this tools lint-like feedback, I was able to go into iTunes and edit the info for offending songs and make my data clean. Making even recreational tasks squeeky clean is alive in the lab. Go to the original post...