Mastering Data Cleaning with a Global Magazine Dataset Using SAS & R
From Global Magazine Rankings to Enterprise-Ready Intelligence: Cleaning the Best Magazines in the World Dataset Using SAS and R 1.Business Crisis Scenario A global publishing company prepared an executive dashboard ranking the Best Magazines in the World based on circulation, subscription revenue, readership, and editorial category. During quarterly reporting, executives discovered duplicate magazine IDs, invalid launch dates, inconsistent country names, missing circulation values, malformed publisher emails, and negative subscription prices. These issues produced incorrect rankings, misleading AI predictions, inaccurate revenue forecasts, and unreliable dashboards. In regulated industries such as clinical research, similar problems can delay regulatory submissions and compromise SDTM or ADaM deliverables. Therefore, enterprise data cleaning is not simply cosmetic it is the foundation of trustworthy analytics. 2.Raw Dataset Variable Description ...