The project is part of an auspicious internal research project for enhancing Business Intelligence (BI) solutions on existing platforms. By enhancing those platforms with Statistical Disclosure Control (SDC), iRiX Software Engineering AG can gain competitive advantage in the field of Business Intelligence. Especially the branch-independent approach of SDC has been successfully tied to iRiX Software Engineering AG’s business model. The final implementation will work fully automated without any human intervention required at all. Other benefits include trust in data management from clients to manage highly valuable data. SDC also shows accountability for data risk abuse which is another highly appreciated factor from clients. The primary driver is balancing the interest between International Air Transport Association (IATA) and its CargoIQ members. On the one side, IATA want to protect their CargoIQ members from disclosing each other. Other CargoIQ members want at the same breath to be protected while also asking for comprehensive and detailed information for the CargoIQ platform.

General Static Business Process Modelling (GSBPM) from www.unece.org is applied as a framework throughout the bachelor thesis. All stages are included to ensure proper problem solving. Each GSBPM stage is prudently documented. Its influences on the following chapter in a coherent way, which provides the reader a common thread to the end. Although few literatures were helpful, the approach is similar to approach the disclosure risk as a malicious user. Out of this approach, the approach was highly effective to find unknown pitfalls which are all properly documented.

The results encompass the finding of suitable Statistical Disclosure Control (SDC) software. This decision is based on a thorough system architecture analysis. Also, the next steps for the implementation of sdcMicro is provided which needs slight technical adaptions to deploy sdcMicro in a productive environment. The starting rules for SDC implementation are defined and during operation to be adapted. What is more, initial data safeguards are complemented by protection on a record level. The combination of data safeguards and sdcMicro are combined in a single R script which provides the ideal foundation for integrational work after this thesis. Next, several test sets are chosen from the client web platform (CargoIQ) as well as local data to gain insightful perspectives about the data behaviour before and after SDC application. Finally, an action-plan based on Eisenhower matrix is provided to ensure proper action taking.