Challenges in data analysis due to Demonetization

We are all aware of demonetization and its ongoing impact in the entire country. Government is trying hard to digitalize entire financial system. In nutshell, initially to create lower cash transaction before reaching to complete cashless transaction. Use of different types digital wallet, mobile banking, debit and credit cards are started booming among the people of the country and citizens slowly started adopting it mainly to get rid of long queues in ATM, Banks and due to their advantages of facilities, usability over traditional cash transactions. Of course, it will take time to reach  the grass root level to achieve digital transaction.
If we see from the technological perspectives, very huge data will be generated once digitalization penetrate to deeper. This data is nothing but the complete digital information about transaction from POS/Mobile wallet/M- Banking/Cards to actual banking system and subsequently to the receiver or vice versa.

We need a very smart technology to challenge this data tsunami from the analysis angle. With efficient big data tools, it is possible for the systems to handle and analyse. Distributed data storage mechanism and parallel processing of data has to be adopted to get all the desired information because 90% of data always lies in motion in digital cash translation.

Interestingly, Indian Railways have implemented Pivotal GemFire, a distributed in-memory database for revamping the IRCTC website. Pivotal GemFire is a product that has been release to the market by customizing the components of Hadoop.