A Rule Based Data Cleansing Pipeline for Automated Data Import in the Context of Social Clubs

Managing the member data of social clubs can be a tedious task. However, there are software solutions available that can help streamline this process. This although means, that existing member data, that is often in the form of text-based data formats like CSV, or semi-structured formats like XML, or Excel needs to be imported in those tools. Unfortunately, the data in these formats may contain errors, inconsistencies, and missing values, which can compromise the usability of this data. In this work, a rule-based data cleansing pipeline designed to clean, enrich, and transform social club member data into a suitable format for import into software solutions is presented. The approach is evaluated on a small data sample and shows promising results for such an application scenario.