The Twelve Days of Data Science Gone Wrong
Too often data science journeys look good on paper but go off the rails in practice. The article breaks down common pitfalls — from ignoring data quality to over‑complicating models — and shows why success starts with fundamentals, clear problems, and business alignment. Without those, even the smartest algorithms deliver little value.