Research of Big Data Based on the Views of Technology and Application

Abstract

In the era of big data, large amounts of data affect our work, life and study, even national economic development. It provides a new way of thinking and approaches to analyze and solve problems, which gradually becomes a hot research. Based on describing the concept and characteristics of big data, this paper describes the development of technologies in big data analysis and storage and analyses the trends and different values in commercial applications, manufacturing, biomedical science and other applications. At last, the authors sum up the existent challenges of big data applications and put forward the view that we should deal with big data challenges correctly.

Share and Cite:

Mo, Z. and Li, Y. (2015) Research of Big Data Based on the Views of Technology and Application. American Journal of Industrial and Business Management, 5, 192-197. doi: 10.4236/ajibm.2015.54021.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Sina Technology, IT Industry (2015)
http://tech.sina.com.cn/it/2013-09-02/11088699338.shtml
[2] Church, A.H. and Dutta, S. (2013) The Promise of Big Data for OD: Old Wine in New Bottles or the Next Generation of Data-Driven Methods for Change. OD Practitioner, 45, 23-31.
[3] Wikipedia (2015) Big Data.
http://en.wikipedia.org/wiki/Bigdata
[4] Mayer-Schönberger, V. and Cukier, K. (2013) Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt, Boston.
[5] Gobble, M.M. (2013) Big Data: The Next Big Thing in Innovation. Research-Technology Management, 56, 64-67.
http://dx.doi.org/10.5437/08956308X5601005
[6] Dean, J. and Ghemawat, S. (2008) MapReduce: Simplified Data Processing on Large Clusters. Communications of the ACM, 51, 107-113.
http://dx.doi.org/10.1145/1327452.1327492
[7] Xu, X.B., Yang, Z.Q., Xiu, J.P. and Chen, L.I.U. (2013) A Big Data Acquisition Engine Based on Rule Engine. The Journal of China Universities of Posts and Telecommunications, 20, 45-49.
http://dx.doi.org/10.1016/S1005-8885(13)60250-2
[8] Castiglione, A., Gribaudo, M., Iacono, M. and Palmieri, F. (2014) Exploiting Mean Field Analysis to Model Performances of Big Data Architectures. Future Generation Computer Systems, 37, 203-211.
http://dx.doi.org/10.1016/j.future.2013.07.016
[9] Renu, R.S., Mocko, G. and Koneru, A. (2013) Use of Big Data and Knowledge Discovery to Create Data Backbones for Decision Support Systems. Procedia Computer Science, 20, 446-453.
http://dx.doi.org/10.1016/j.procs.2013.09.301
[10] Ribarsky, W., Wang, D.X. and Dou, W. (2014) Social Media Analytics for Competitive Advantage. Computers & Graphics, 38, 328-331.
http://dx.doi.org/10.1016/j.cag.2013.11.003
[11] Hipgrave, S. (2013) Smarter Fraud Investigations with Big Data Analytics. Network Security, 2013, 7-9.
http://dx.doi.org/10.1016/S1353-4858(13)70135-1
[12] Lee, J., Lapira, E., Bagheri, B. and Kao, H.A. (2013) Recent Advances and Trends in Predictive Manufacturing Systems in Big Data Environment. Manufacturing Letters, 1, 38-41.
http://dx.doi.org/10.1016/j.mfglet.2013.09.005
[13] Noor, A. (2013) Putting Big Data to Work. Mechanical Engineering, 135, 32-37.
[14] O’Driscoll, A., Daugelaite, J. and Sleator, R.D. (2013) ‘Big Data’, Hadoop and Cloud Computing in Genomics. Journal of Biomedical Informatics, 46, 774-781.
http://dx.doi.org/10.1016/j.jbi.2013.07.001
[15] Narula, J. (2013) Are We Up to Speed? From Big Data to Rich Insights in CV Imaging for a Hyperconnected World. JACC: Cardiovascular Imaging, 6, 1222-1224.
http://dx.doi.org/10.1016/j.jcmg.2013.09.007
[16] Mack, S.J. (2013) Human Immunology in the Era of Big Data. Human Immunology, 75, 2-3.
http://dx.doi.org/10.1016/j.humimm.2013.12.002
[17] Hoffmann, L. (2013) Looking Back at Big Data. Communications of the ACM, 56, 21-23.
http://dx.doi.org/10.1145/2436256.2436263
[18] Steed, C.A., Ricciuto, D.M., Shipman, G., Smith, B., Thornton, P.E., Wang, D., Williams, D.N., et al. (2013) Big Data Visual Analytics for Exploratory Earth System Simulation Analysis. Computers & Geosciences, 61, 71-82.
http://dx.doi.org/10.1016/j.cageo.2013.07.025
[19] Cumbley, R. and Church, P. (2013) Is “Big Data” Creepy? Computer Law & Security Review, 29, 601-609.
http://dx.doi.org/10.1016/j.clsr.2013.07.007
[20] Nunan, D. and Di Domenico, M. (2013) Market Research and the Ethics of Big Data. International Journal of Market Research, 55, 505-520.
http://dx.doi.org/10.2501/IJMR-2013-015

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.