Another methodology is Sample, Explore, Modify, Model, and Assess (SEMMA). SEMMA describes the main modeling tasks in data science, while leaving aside business aspects such as data understanding and deployment. SEMMA was developed by SAS Institute, which is one of the largest vendors of statistical software, aiming to help the users of their software to carry out core tasks of data mining.