Comprehensive Study on Big Data Analytics
Keywords:
Big Data, Big Data Analytics, Hadoop, Map ReduceAbstract
Big Data is termed has any type of datasets which are so vast and compound which becomes difficult to process them using traditional data processing applications. While handling vast dataset different challenges may be faced by the user. In recent times, the internet application and communication have observed a lot of growth and reputation in the field of Information Technology. These internet applications and communication are frequently generating the large size, different variety and with some authentic difficult multifaceted structure data called big data. As a result, we are now in the era of enormous automatic data collection. For example, E-commerce transactions include activities such as online buying, selling or investing. Thus they generate the data which are high in dimensional and complex in structure. The traditional data storage techniques are not adequate to store and analyses those huge volume of data. Many researchers are doing their research in dimensionality reduction of the big data for effective and better analytics report and data visualization. The technologies used by big data application to handle the massive data are Hadoop, Map Reduce, and Apache Hive. Hence, the aim of the survey paper is to provide the overview of the big data analytics, issues, challenges and various technologies related with Big Data.
References
[1] Yuri Demchenko, “The Big Data Architecture Framework (BDAF)”, Outcome of the Brainstorming Session at the University of Amsterdam 17 July 2013.
[2] Amogh Pramod Kulkarni, Mahesh Khandewal, “Survey on Hadoop and Introduction to YARN”, International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 5, May
2014).
[3] M. R. Berthold, N. Cebron, F. Dill, T. R. Gabriel, T. Kötter, T. Meinl, et al., “KNIME: The Konstanz Information Miner”, in Data Analysis, Machine Learning and Applications (Studies in Classification, Data Analysis, and Knowledge Organization), Springer Berlin Heidelberg, pp. 319–326, 2008.
[4] Sagiroglu, S.Sinanc, D.,”Big Data: A Review”,2013, 2024.
[5] Ms. Vibhavari Chavan, Prof. Rajesh and N. Phursule, “Survey Paper On Big Data”, International Journal of Computer Science and Information Technologies, Vol. 5 (6), 2014.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
