Big Data In Aviation
Advances in technology have increased our ability to collect, store and analyze data. Big data emerged due to the following three major trends. First, it has become easier to generate data due to smart devices, Internet of things, sensors etc and all this being stored at a minimal cost. Second, it is easier to process this huge amount of data due to cloud computing, multi core CPUs etc. Thirdly, many people have ways and access to this data and use it for valuable decision making.
The most popular definition of Big Data can be defined as volume, velocity and variety of data. Volume refers to the size of data sets and storage, velocity is the speed of incoming data and variety is the data types. Business has always wanted to derive insights from Big Data for faster and better decision making. The aviation industry deals with huge amounts of data and many airports cannot manage the amount of data they receive. Data from various sources such as passenger flow, weather conditions, sensors, cost reduction, departure and arrival timings, services and feedback, revenue enhancement etc.From a recent study conducted by a leading
software company, big data analytics has become the highest priority for aviation (61%) followed by wind (45%) and manufacturing (42%) companies. indexThere are about 35 million flight departures per year and it is very important for decision making by airports and airlines. Data collection could be effectively used by the airline websites with respect to transactional data sets and booking. A study shows that there are greater than $140 million ticket transactions made through airline ticketing websites. The current look to book ratio stands to 10:1 which says that a person would look up to 10 websites before booking an airline ticket.
However, airlines do not track this data. They record only their transactional data which leads to them missing out on possible marketing strategies. Tracking the IP address, time and fares offered by other websites would
allow the airlines a greater insight into its customer needs. The simplest example can be route development where airlines can see if a customer searched for a route it does not offer.Over the past two decades the rise of a new industry too place whose main asset is data. The use of this vast amount of data occurs in Internet-based industries.
A study by FAA states that during a year a jet engine generates data equivalent to 20TB. Most of this data is not used for any analytics purpose since this data is unstructured .Big data analytics can be used to predict the fault in the component by analysing data obtained from various sensors.
Big data can help operations for airline companies and airports to reduce redundant variability. Using the data, airlines can offer personalized incentive for every type of customer resulting in more auxiliary sales and greater percentages of repeat business.