Submit your paper : editorIJETjournal@gmail.com Paper Title : Relevance of big data research and related challenges: a survey ISSN : 2395-1303 Year of Publication : 2021 10.29126/23951303/IJET-V7I1P5 MLA Style: -Ms. Anushree Negi " Relevance of big data research and related challenges: a survey " Volume 7 - Issue 1(41-50) January - February,2021 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -Ms. Anushree Negi " Relevance of big data research and related challenges: a survey " Volume 7 - Issue 1(41-50) January - February,2021 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract - Throughout the age of technology, huge amounts of data are accessible to decision-makers on hand. Besides, decision-makers need to gain relevant knowledge from these diverse and constantly changing data, from everyday transactions to user interactions and networking site data. It can be delivered using Big Data Analytics, which is the implementation of data analysis methods to Big Data. Big Data corresponds to data which are not only huge, as well as broad in variety and size, making them difficult to process using typical methodologies. The application of these data involves a great deal of work for successful decision-making at several levels of information extraction. We discuss the meaning of big data in this paper including its characteristics, and importance. Then we recognize the meaning and possibilities Big data brings to us from diverse perspectives. First, we're introducing descriptive big data projects from all around the world. We identify the significant challenges in big data and its analysis, as well as possible alternatives to such difficulties and also bring out overview of few tools for Data processing. Lastly, we summarize the paper by putting forth some proposals on the execution of big data initiatives. Reference [1. M. K. Kakhani, S. Kakhani and S. R.Biradar, Research issues in big data analytics, International Journal of Application or Innovation inEngineering &Management, 2(8) (2015), pp.228-232. 2. W.B. Arthur, The second economy, available at: http://www.images-et-reseaux. com/sites/default/files/medias/blog/2011/12/the-2nd-economy.pdf, 2011. 3. V. Mayer-Schonberger, K. Cukier, Big Data: A Revolution That Will Transform How We Live, Work, and Think, Houghton Mifflin Harcourt, 2013. 4. T. Hey, S. Tansley, K. Tolle (Eds.), The Fourth Paradigm: Data-Intensive Scientific Discovery, Microsoft Corporation, 2009. 5. J. Ginsberg, M.H. Mohebbi, R.S. Patel, L. Brammer, M.S. Smolinski, L. Brilliant, Detecting influenza epidemics using search engine query data, Nature 7232 (2009) 1012–1014. 6. [20] Big data for development: challenges & opportunities, available at: http:// www.unglobalpulse.org/projects/BigDataforDevelopment, May 2012. 7. A. Jacobs, The pathologies of big data, Communications of the ACM, 52(8) (2009), pp.36-44. 8. H. Zhu, Z. Xu and Y. Huang, Research on the security technology of big data information, International Conference on Information Technology Management Innovation, 2015, pp.1041-1044. 9. Z. Hongjun, H. Wenning, H. Dengchao and M. Yuxing, Survey of research on information security in big data, Congress da sociedada Brasileira de Computacao, 2014, pp.1-6. 10. I. Merelli, H. Perez-sanchez, S. Gesing and D. Agostino, Managing, analyzing, and integrating big data in medical bioinformatics: open problems and future perspectives, BioMed Research International, 2014, (2014), pp.1-13. 11. Bhosale, Harshawardhan S., and Devendra P. Gadekar. "A review paper on big data and hadoop." International Journal of Scientific and Research Publications 4.10 (2014): 1-7. 12. Pol, Urmila R. "Big data and hadoop technology solutions with cloudera manager." International Journal 4.11 (2014). 13. Kumar, Ajay, et al. "A big data MapReduce framework for fault diagnosis in cloud- based manufacturing." International Journal of Production Research 54.23 (2016): 7060-7073. 14. Rangra, Kalpana, and K. L. Bansal. "Comparative study of data mining tools." International journal of advanced research in computer science and software engineering 4.6 (2014). 15. Berger, Charlie. "Oracle Advanced Analytics: Oracle R Enterprise & Oracle Data Mining." Product Presentation(2012): 1-58. 16. S. Del. Rio, V. Lopez, J. M. Bentez and F. Herrera, on the use of mapreduce for imbalanced big data using random forest, Information Sciences, 285 (2014), pp.112- 137. Keywords bigdata, datamining, analytics, decision making, Hadoop. |