Role of Big Data in Business and Information Technology
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This paper aims to evaluate the significance of the impact of big data in various fields and determine its future in those areas. A comprehensive review of literature on influence and trends of big data variables with respect to different fields built hypothetical foundation of the paper. The big data is a tremendous amount of structured and unstructured data that provides major insights into a particular field which further supports the decision-making systems and builds the foundation of company’s competitiveness. Data contributes in the processing, evaluation, understanding and decision-making steps. Big data influences every area that constitutes of pools of data. This proposed paper is beneficial to accumulate the knowledge regarding the hidden patterns and insights of big data variables and assess the value of it in major areas such as business and information technology.
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References
-
Krishnan, K. (2013). Data Warehousing in the Age of Big Data. San Francisco, UNITED STATES: Elsevier Science & Technology.
Google Scholar
1
-
Zakir, J., Seymour, T., & Berg, K. (2015). BIG DATA ANALYTICS. Issues in Information Systems, 16(2).
Google Scholar
2
-
John Walker, S. (2014). Big data: A revolution that will transform how we live, work, and think. In: Taylor & Francis.
Google Scholar
3
-
Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85-99.
Google Scholar
4
-
Cukier, K., & Mayer-Schoenberger, V. (2013). The rise of big data: How it's changing the way we think about the world. Foreign Aff., 92, 28.
Google Scholar
5
-
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity.
Google Scholar
6
-
Yang, X., Lu, R., Liang, H., & Tang, X. (2015). Big data research.
Google Scholar
7
-
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165-1188.
Google Scholar
8
-
Logica BANICA, A. H. (2015). BIG DATA IN BUSINESS ENVIRONMENT. Buletin ştiinţific: Universitatea din Piteşti. Seria Ştiinţe Economice, 14(1), 79-86.
Google Scholar
9
-
Alfouzan, H. I. (2015). Big Data In Business. International Journal of Scientific & Engineering Research, 6(5), 1351.
Google Scholar
10
-
Gopalkrishnan, V., Steier, D., Lewis, H., & Guszcza, J. (2012). Big data, big business: bridging the gap. Paper presented at the Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications.
Google Scholar
11
-
Fan, W., & Bifet, A. (2013). Mining big data: current status, and forecast to the future. ACM sIGKDD Explorations Newsletter, 14(2), 1-5.
Google Scholar
12
-
Mithas, S., Lee, M. R., Earley, S., Murugesan, S., & Djavanshir, R. (2013). Leveraging Big Data and Business Analytics [Guest editors' introduction]. IT professional, 15(6), 18-20.
Google Scholar
13
-
Data, B., & Intelligence, B. (2014). TECHPractices.
Google Scholar
14
-
Karjoth, G., Schunter, M., & Waidner, M. (2002). Platform for enterprise privacy practices: Privacy-enabled management of customer data. Paper presented at the International Workshop on Privacy Enhancing Technologies.
Google Scholar
15
-
Davenport, T. H., & Dyché, J. (2013). Big data in big companies.
Google Scholar
16
-
Alam, J. R., Sajid, A., Talib, R., & Niaz, M. (2014). A review on the role of big data in business.
Google Scholar
17
-
IBM, Zikopoulos, P., & Eaton, C. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data: McGraw-Hill Osborne Media.
Google Scholar
18
-
Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey quarterly, 56(1), 75-86.
Google Scholar
19
-
Davenport, T. H., Barth, P., & Bean, R. (2012). How big data is different. MIT Sloan Management Review, 54(1), 43.
Google Scholar
20
-
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication & society, 15(5), 662-679.
Google Scholar
21
-
Xu, L., Jiang, C., Wang, J., Yuan, J., & Ren, Y. (2014). Information security in big data: privacy and data mining. IEEE Access, 2, 1149-1176.
Google Scholar
22
-
Mell, P., & Grance, T. (2011). The NIST definition of cloud computing.
Google Scholar
23
-
Schadt, E. E., Linderman, M. D., Sorenson, J., Lee, L., & Nolan, G. P. (2010). Computational solutions to large-scale data management and analysis. Nature reviews. Genetics, 11(9), 647-657. doi:10.1038/nrg2857
Google Scholar
24
-
Chen, C. P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347.
Google Scholar
25
-
Agrawal, D., Das, S., & El Abbadi, A. (2011). Big data and cloud computing: current state and future opportunities. Paper presented at the Proceedings of the 14th International Conference on Extending Database Technology.
Google Scholar
26
-
Hand, D. J. (2007). Principles of data mining. Drug safety, 30(7), 621-622.
Google Scholar
27
-
Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: for marketing, sales, and customer relationship management: John Wiley & Sons.
Google Scholar
28
-
Freitas, A. A. (2001). Understanding the crucial role of attribute interaction in data mining. Artificial Intelligence Review, 16(3), 177-199.
Google Scholar
29
-
Sreedhar, C., Kavitha, D., & Rani, K. A. Big Data and Hadoop. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume, 3.
Google Scholar
30
-
Bhosale, H. S., & Gadekar, D. P. (2014). A review paper on Big Data and Hadoop. International Journal of Scientific and Research Publications, 4(10), 1-7.
Google Scholar
31
-
Yang, X. Y., Liu, Z., & Fu, Y. (2010). MapReduce as a programming model for association rules algorithm on Hadoop. Paper presented at the Information Sciences and Interaction Sciences (ICIS), 2010 3rd International Conference on.
Google Scholar
32
-
De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. Paper presented at the AIP conference proceedings.
Google Scholar
33
-
Wang, Y., & Hajli, N. (2017). Exploring the path to big data analytics success in healthcare. Journal of Business Research, 70, 287-299. doi:https://doi.org/10.1016/j.jbusres.2016.08.002
Google Scholar
34
-
di Bella, E., Leporatti, L., & Maggino, F. (2018). Big Data and Social Indicators: Actual Trends and New Perspectives. Social Indicators Research, 135(3), 869-878. doi:10.1007/s11205-016-1495-y
Google Scholar
35
-
Chaudhari, P., & Patel, B. (2017). Future of Big Data. International Research Journal of Engineering and Technology, 4(1), 595-597.
Google Scholar
36
-
Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1-14. doi:10.1007/s10708-013-9516-8
Google Scholar
37
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