Author : Kavyashree. J 1
Date of Publication :30th November 2017
Abstract: In today’s world of Investment Banking and other financial domain areas, the requirement and demand for the automation in data processing is very high. The data is accumulated from different data sources with an increase in the rules and regulations, but that should also come with a plan of cost reduction without compromising in quality and scalability. The underlining technologies that handle big data with should guarantee of optimization and also keep global financial institutions interest in it. So this paper or case study covers the Big Data architecture and design that would help banking institutions make key decisions. We have used Hadoop map-reduce and no-SQL flexibility also maintaining the quality, banking rules and standards. The data that is proposed to be consumed or used for this analysis is from different sources and techniques, techniques that are followed in regular banking practices. That would include “front end†or “backend data processingâ€. Business process modelling would require data transmission OR orchestration from different sources that are required to make key and important financial decisions.
Reference :