This thesis analyzes the characteristic air traffic time series data of European aviation industry by using wavelet decomposition. Firstly, time frequency representation and discrete time wavelet decomposition is introduced by giving some theoretical background and basic definitions. Then, the attributes of AEA data, i.e. load factor, available seat kilometer and revenue passenger kilometer is analyzed both geographically and based on prominent Airline operators. Furthermore, their relative comparisons have led to unravel some underlying implications and their distinctive interpretations for the airline industry