An application of business intelligence techniques in the civil aviation cargo planning

Civil aviation has been growing 5 % per year since 1980 all over the world while in Turkey there has been 15% of growth over the last decade. Moreover, airlines in developed countries have adapted several business intelligence and analytics implementations in order to support their decision-making activities. However, this adoption has not satisfactorily achieved in developing countries such as Turkey. Especially, applied business intelligence studies as well as the academic research in this field have remained insufficient in those countries. The aim of this study is to put forth the different types of BI applications in civil aviation sector. Therefore, the data have been obtained from the airline company was analyzed in order to demonstrate different levels of business analytics. Analyses of the thesis include different analytics from descriptive to prescriptive in order to profile the data of international passenger's baggage. After the completion of data preprocessing steps, multidimensional analysis has been made and special outcomes were put forward. Following that, selected data mining techniques have implemented like clustering and association rules in predictive context. Lastly, using the outcome which is acquired from predictive analytics was supported by DEMATEL method that is one of the noteworthy multi-criteria decision-making methods and prescriptive analytics techniques. Consequently, effective regional differences were tried to obtain from passenger baggage profiles. This study also included with some real-world application examples, contributes both flight planning and cargo departments in the air transportation sector by setting an example for different levels of analytics in the academic sense.