Open AccessAn Efficient System to Predict and Analyze Stock Data using Hadoop Techniques
Author(s) -
Jithina Jose,
Suja Cherukullapurath Mana,
B. Keerthi Samhitha
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1824.078219
Subject(s) - enthusiasm , computer science , stock (firearms) , inflow , database , stock exchange , operations research , business , finance , engineering , mechanical engineering , psychology , social psychology , physics , mechanics
Stocks, they assume significant job in keeping up the capital inflow of an organization or to keep up the business of the nation. As indicated by certain reports, 1.46 billion exchanges are done every day in NYSE. Increment of open enthusiasm on the promoting came about to expand the stock exchanges flawlessly. Because of the expansion of number of exchanges one can abuse the information and the examples which exists in the information by applying present day strategies like HDFS(Hadoop Distributed File System) .Taking the upside of size of the information and by allocating information to dispersed frameworks one can accomplish the plots from the information and when this procedure is done powerfully it can give an estimation of future examples