In QDeFuZZiner software, the fundamental unit is referred to as a project, which encompasses the definitions of two source datasets for import and analysis, known as the "left dataset" and "right dataset." Each project not only includes these datasets but also a variable number of solutions that detail the methodology for conducting fuzzy match analysis. Upon creation, every project is assigned a distinct project tag, which is subsequently appended to the names of the corresponding input tables during the raw data import process. This tagging system guarantees that the imported tables maintain uniqueness through association with their respective project names. Furthermore, during the import phase and later when generating and executing solutions, QDeFuZZiner establishes various indexes on the PostgreSQL database, thereby enhancing the efficiency of fuzzy data matching procedures. The datasets themselves can be sourced from spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma separated values) flat files, which are uploaded to the server database, leading to the creation, indexing, and processing of the associated left and right database tables. This structured approach not only simplifies data management but also streamlines the analysis process, making it easier for users to derive insights from their datasets.