Abstract
Aiming at the practical questions of airline companies, such as the platform used to analyze the QAR data is not unified, lots of missing values, duplicate records and noise data in decoded QAR data, which seriously affect the efficiency of analysis of the QAR data. Thus, in this paper we present to analyze the data by designing QAR data warehouse, describe how to define the QAR data subjects, put forward a star schema, propose a cleaning framework of data preprocessing based on subjects and introduce the cleaning methods that are appropriate to QAR data and design multidimensional model by ETL, implement the farther research on QAR data through analyzing exceed the limits, so this can improve flight character and factor of safety for airline companies.
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