Cleaning the World's Soundtrack: Advanced SAS and R Techniques for Reliable Music Analytics
From Symphony to Statistics: Transforming Global Music Data into Trusted Analytical Intelligence with SAS and R Introduction:The Business Crisis Nobody Expected A global music streaming company launched an AI recommendation engine intended to increase subscriber engagement across continents. Instead, the platform began recommending classical Indian ragas to heavy metal listeners, African Afrobeat to K-Pop fans, and duplicate royalty payments were issued to artists because duplicate track IDs existed in production systems. Executives discovered serious data quality failures: Duplicate music identifiers Missing release dates Negative streaming revenue values Invalid listener ages Corrupted genre labels Broken email addresses Region code inconsistencies Invalid timestamps Mixed uppercase and lowercase artist names Embedded whitespace corruption NULL strings stored as actual text The result was devastating: AI recommendation failures In...