ANALYZING FINANCIAL DATA AND MUTUAL FUNDS RECOMMENDATION BY USING BIG DATA ANALYTICS (PROPOSED ANALYSIS OF STOCK MARKET)

Abstract

Big data analytics is the process of examining large and varied data sets -- In this paper, we analyze the financial
data for making prediction in mutual funds by using big data analytics and recommend the user investment in various
category mutual funds based on user details. Hadoop is a free , java-based programming framework which is widely used
big data processing engine. It supports the processing of large data sets in a parallel and distributed computing environment.
Our technique focused on all strategies such as computer hardware ,data processing ,prediction method, etc .we mainly
consider the market dataset on National Stock Exchange(NSE) and Bombay Stock Exchange(BSE) based companies sectors
such as Banking, Automobiles, Energy, Software and Moving Consumer Good(FMCG).Huge Collection of data is retrieved
from open source datasets that are available from major Application Providers. The analysis would be completed before the
user search any sector Mutual funds for investment, the process of financial data’s Map Reduce function Grouping classified
in data wise, month wise and year wise. We will get find out each and every companies Profit level in all the year within a
seconds. Preprocessing is a backend job that entire sector is mapped. User’s financial details are available on form 16
which is already filled by user in login phase, we calculate the risk factor for each company and recommend the investment.
Our application going to guide the user Mutual Fund Investment which is based on user requirements .It is fully based on
user credentials not a company profit over the year