Possibilities of Using Predictive Analytics in the Aviation Industry - Case Study

Predictive analytics allows businesses to predict the future with a certain degree of accuracy. Forecasting the future development of the business and the direction of the business was and is still essential. In today’s turbulent world, prediction has become critical for effective business and futureproofing, and it is reaching its peak in the priorities of individual companies today. The reason for the need for predictive analytics is that companies have to face serious business and supply chain disruptions, sudden changes in demand, and new risks or challenges. Acceptable and accurate forecasts are essential for making adequate decisions in a world where rapid changes and market fluctuations are constant. In the presented article an ARIMA model (created in Python) to forecast gross capital expenditures is used. Based on the results, it was shown that the ARIMA(1,1,1) model is the most suitable model for forecasting air passenger traffic.