How does Big Data help kentkart make public transport better?


Nowadays, in the era of digitalization, the information flow is as intensive and valuable as never before. Big Data refers to this ever-increasing accumulation of large and complex sets of information from different sources. Technology giants are all focusing on big data collection because of its importance for business. With the spread of smartphones, social media, and different online platforms immense amounts of information are produced, collected and analyzed every second. It is clear that information is an incredible source of power and revenue for a lot of companies worldwide. To better explain how Kentkart processes big data, let’s take a look at its five components, the so-called 5Vs of big data.


Variety describes a wide variety of unstructured data collected from different technologies, in different formats.

Volume refers to extremely large amounts of information collected. Kentkart systems gather such data of its every project 24/7 from the mobile application, Validators, and Terminal devices.

Velocity describes the extremely high speed of big data production. Each of our vehicles generates 1 GPS event data in an average of 5 seconds, and if we count that different event data are generated at the same time, a minimum of 15,000 event records are created by a single vehicle in one day. That means millions of data sets are shared with the system in one day. And thanks to cloud-based technologies this is all done in real time!

Veracity means that the flow of such diverse, fast, and big data must be at the right layers and at the required level of security and privacy. While all our data is transferred to the system, it passes through the security layers we have determined, and at the same time, communication with the server is provided with certain protocols within the scope of IoT.

Value is the most important component of big data and it expresses how valuable this data is for our institution and our customers. With this data, we apply various analysis methods to ensure that our customers can make the right decisions at critical points. For example, we have alarm controls for route violations, speeding, and aggressive driving all thanks to our GPS data processing. All of our data is collected on Apache Kafka, transferred to the system as raw, then we use tools like Apache Flink and Apache Spark for instant data analysis.

Written by Baran Kaya

Senior Software Engineer at kentkart