In his Top 10 Data Mining Mistakes John Elder shares lessons learned from more than 20 years of data science consulting experience. Avoiding these mistakes are cornerstones to any successful analytics project. In this blog about Mistake #4 you will learn that inducing models from data has the virtue of looking at the data afresh, not constrained by old hypotheses. But, while “letting the data speak”, you must be careful not to tune out received wisdom, because often, nothing inside the data will protect one from significant, but wrong, conclusions.