Many attempts have been made to derive insights and any useful information about the behavior of the passengers traveling using different data analytics approaches and techniques. The different ways the researchers have tried to model the travel behavior and also their attempt to measure the behavioral changes at an individual level will be discussed in this chapter. The insights derived using these methods can help policy makers and the authorities to make necessary and important changes to the railways. The transit systems of the Railways provide us with the data, which is analysed using different techniques and methodologies and derived insights from.
TopIntroduction
Big Data is the new frontier, the frontier which encompasses the leading technologies for collecting and then analyzing data. This analyzed data is then turned into usable information which the management of an organization can use to take decisive actions. Big Data is the result of the continuous evolution of data analytic techniques which have been in existence for decades but were not of practical use due to lack of computational power. With the increased computational power, reduced prices for storing data and huge amounts of data available and collected from all the devices and the progress in the technological sector, the use of these analytic techniques has become practical.
Big Data is any data or technique which can be associated with the 4 V’s, which are Volume, Variety, Velocity and Value. It can be defined as a combination of software and hardware which are able to handle input data, which can be structured, semi-structured or un-structured into an algorithm or a model at high speed and be able to derive useful information from it in a timely manner (Hilbert & Martin 2015).
The Data Acquisition is governed by the 4 V’s and can be understood as the process of not only collection of data, but also filtering and cleaning or that data before it is stored and is the first and the most important part of Big Data (Lyko & Klaus, 2016). It doesn’t matter how much data you have collected, how many different sources you have used for collecting data or over how long a period if the quality of data is poor, all algorithms and models will also output poor results. Many researchers have stated in their literary works of how the poor data quality has a significant negative impact on any organization’s efficiency and that good quality data plays a part in the success of companies (Madnick et al., 2004; Haug et al., 2009; Even & Shankaranarayanan, 2009). In this chapter smartcards used in railway systems will be discussed as a source of collecting good quality and accurate data regarding the passengers as compared to surveys.
Since the turn of the century, our ability to produce data has increased exponentially. More and more people have access to the internet, new innovations in the field of communication, smart phones, Internet of Technology (IOT) have all contributed substantially to the huge amounts of data that are being generated on a daily basis in the form of health records of patients, transactional data present with the banks, digital prints of people surfing on the internet. But the evolution in the technologies of computation and data storage, which have enabled the computer scientists and statisticians alike, are the reason that they are able to make sense from these huge amounts of data. This Data and the increased computational capabilities have helped doctors make strides in the field of treatment of diseases like Cancer, study the Human genome, reduce the timeline for development of and for testing of new drugs. Big data has helped the banks around the world to detect and/ or avert frauds, money laundering and make banking safer. It has played an important role in reducing the cost of numerous companies around the world and made their processes more efficient and hence more profitable. It has helped companies like Amazon, Google and Netflix know what their customers like and predict their preferences and what to suggest to their customers. Big Data now has started having a huge impact on how we travel using the public transportation systems like Railways and Airlines (https://hortonworks.com/blog/big-data-public-transportation/). Big Data and how it is affecting Railways and its interaction with its passengers will be specifically discussed in this paper.
Big Data and its analytics techniques can be and need to be applied to huge amounts of data which is being produced by the various aspects and elements of Railways including the millions of people who are travelling long distances, ticket reservations being made, locomotives and freight cars, vendor management, dealing with the goods and freights being loaded, dispatched and unloaded and the thousands of staff working around the country in this sector (Jose, 2016).