SEMMA is an acronym that stands for Sample, Explore, Modify, Model, and Assess. It is a list of sequential steps developed by SAS Institute, one of the largest producers of statistics and business intelligence software. It guides the implementation of data mining applications.[1] Although SEMMA is often considered to be a general data mining methodology, SAS claims that it is "rather a logical organization of the functional tool set of" one of their products, SAS Enterprise Miner, "for carrying out the core tasks of data mining".[2]
In the expanding field of data mining, there has been a call for a standard methodology or a simple list of best practices for the diversified and iterative process of data mining that users can apply to their data mining projects regardless of industry. While the Cross Industry Standard Process for Data Mining or CRISP-DM, founded by the European Strategic Program on Research in Information Technology initiative, aimed to create a neutral methodology, SAS also offered a pattern to follow in its data mining tools.
The phases of SEMMA and related tasks are the following:[2]
SEMMA mainly focuses on the modeling tasks of data mining projects, leaving the business aspects out (unlike, e.g., CRISP-DM and its Business Understanding phase). Additionally, SEMMA is designed to help the users of the SAS Enterprise Miner software. Therefore, applying it outside Enterprise Miner may be ambiguous.[3] However, in order to complete the "Sampling" phase of SEMMA a deep understanding of the business aspects would have to be a requirement in order to do effective sampling. So, in effect, a business understanding would be required to effectively complete sampling.[4]