450.From Dead Mobile Brands to Clean Data Mastery Using INPUT and PUT in SAS
Mastering INPUT vs PUT Functions in SAS with RealWorld Error Handling : Vanished Mobile Giants to Clean Data Insights 1. Introduction Imagine you are working on a legacy telecom analytics project. Your manager hands you a dataset containing mobile companies that once dominated the market brands that were household names but no longer exist. Sounds simple, right? But the moment you open the dataset, reality hits: Company names are inconsistent (e.g., nokia , NOKIA , Nokia Inc. ) Launch years are missing or incorrectly stored as text Some shutdown years are earlier than launch years Duplicate entries exist Revenue values are stored as characters instead of numeric This is not just messy data it’s dangerous data. In industries like clinical trials or financial analytics , such inconsistencies can lead to: Incorrect statistical conclusions Regulatory rejection Business losses This is where tools like SAS and R become po...