Although new data science and analytics courses and programs launch about every week, most train participants to analyze data that is not representative of the datasets that practitioners encounter in the real world. In this post, Claire Carroll explains why real-world data (and the tools and platforms required to manage and understand it) demands a different skill set than that taught in most universities and bootcamps. She also considers the consequences of data miseducation (for individuals and their employers) and describes how the training course that she and Michael Kaminsky are building will help analysts take on analytics engineering responsibilities.