1. Historical Data

In order to generate predictive models, financial forecasts and analyzing impacts of trading, it is quite essential for the financial services to perform analytics on the large amounts of data accumulated over the years. This data assists in making large market sets that help in increasing the granularity of the analytics and helps them in coming out with a better and more qualitative conclusive analysis that will help them a great deal while making critical decisions.

2. Regulations and Compliance Requirements

The Financial service sector has off late realized the criticality of implementing new regulations and compliance requirements and as a result if pressing more emphasis on governance and risk reporting. This process accumulates larger amounts of data that is required during analysis in order to help them study the current and evolving trends in a better way. This deeper and more transparent analysis results in a sudden data growth that calls the need for implementing big data.

Also Read: VMware's First Dedicated Cloud Offering; vCloud Suite

Also Read: 4 Common Mistakes While Implementing Virtualization