Data Analytics in Aviation Industry
The aviation industry is a sector involving high cost and security concerns. Analytics in this sector has huge potential, as varied data can be collected at each touch point showcasing customer interests. Crucial factors such as weather forecast should be critically analyzed using sophisticated tools to ensure passenger safety. A lot of logistics complexity also lies straight from building an aircraft to safe take–off and landing. Also, since customers pay the highest prices in this form of transport, the same level of satisfaction and experience too is demanded by them. Almost 1% of the world’s GDP is expected to be spent on air transport in 2017. With such humongous money associated with the airline Industry, the difference between a successful airlines and a still struggling to compete airline is just of Data Analytics. Using sophisticated analytical tools airlines try and capture accurate sensor data to optimize the maintenance of aircraft. They use the weather forecasting tools as well to optimize fuel loads on the machine and hence save costs incurred due to weight. They also indentify and collect the unstructured demand information. This helps them to offer higher customer satisfaction and hence differentiate themselves from the rest. Now-a-days airlines are using technologies, such as Hadoop and sophisticated data mining algorithms, to capture such unstructured data.
Security is of utmost importance at any airport. Any disturbance in the normal operation of security activities triggers could trigger an emergency and cause panic, in addition to loss of money and time. This calls for security features which not only monitor and control crowd at the airport and in the peripheral area, but also systems which can detect potential threats automatically and alert the security personnel. Algorithms are being developed and tested to identify questionable passenger behavior such as isolated movements, movement against the flow of traffic, etc. Such smart systems make security monitoring and enforcement easier. Weather conditions is the most critical external factor which affects airline operations. This necessitates the availability of systems which can predict the weather accurately and in a timely manner. Such predictions enable airlines and airport authorities to plan out operations for the upcoming time period. Airlines can prevent passenger inconvenience due to last minute delays or cancellations. Accurate time estimation and geo-location of storms and other hostile weather conditions would enable airlines to control accidents and save lives. Weather analytics uses past data and other factors that affect the overall weather.