Review in Data Stream Mining in Big Data

Padma Priya. R
2020 International Journal for Research in Applied Science and Engineering Technology  
Data stream mining in big data is a process in which large streams of real-time data are processed with the sole aim of extracting insights and useful trends out of it. Streaming data study in real time is fetching the efficient and fastest way to obtain constructive knowledge from what is occurrence now, allowing concern to react quickly when problems emerge to detect new trends helping to recover their performance. In this paper, we have a tendency to reward the theoretical foundations of
more » ... stream in big data analysis and establish potential directions of future analysis. Mining data stream and big data techniques are being reviewed. 408 ©IJRASET: All Rights are Reserved VII. CONCLUSIONS Data streams are active ordered, fast changing and gigantic, immeasurable and infinite sequence of data objects. Big Data grows continually with fresh data and are being generated at all times; hence it requires an incremental computation approach which is able to monitor large scale of data dynamically. In the field of stream data mining for big data and many problems remain to be solved, the application prospect of data mining in cyberspace is very broad, and the research work in this region is presented with high practical value and academic potential. In this paper, we have a tendency to reward the theoretical foundations of data stream in big data analysis and establish potential directions of future analysis. Mining data stream and big data techniques are being reviewed.
doi:10.22214/ijraset.2020.1075 fatcat:bre434jmpbdlza64npysuzza4a