The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Big data: A review
Abstract
Big data is a term for massive data sets having large, more varied and complex structure with the difficulties of storing, analyzing and visualizing for further processes or results. The process of research into massive amounts of data to reveal hidden patterns and secret correlations named as big data analytics. These useful informations for companies or organizations with the help of gaining richer and deeper insights and getting an advantage over the competition. For this reason, big data implementations need to be analyzed and executed as accurately as possible. This paper presents an overview of big data's content, scope, samples, methods, advantages and challenges and discusses privacy concern on it.
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Cites
Madden, S. (2012) · IEEE Internet Computing · doi:10.1109/mic.2012.50 · Cited by 509
Cited by
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Rasheed, A., San, O., & Kvamsdal, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970143 · Cited by 1,952
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019) · British Journal of Management · doi:10.1111/1467-8551.12343 · Cited by 835
Tsai, C.-W., Lai, C.-F., Chao, H.-C., & Vasilakos, A. V. (2015) · Journal of Big Data · doi:10.1186/s40537-015-0030-3 · Cited by 818
Big Data: Survey, Technologies, Opportunities, and Challenges
Khan, N., Yaqoob, I., Hashem, I. A. T., Inayat, Z., Mahmoud Ali, W. K., Alam, M., Shiraz, M., & Gani, A. (2014) · The Scientific World Journal · doi:10.1155/2014/712826 · Cited by 547
Smith, G. (2018) · Journal of Big Data · doi:10.1186/s40537-018-0143-6 · Cited by 532
Metadata
- Authors
- Sagiroglu, S., & Sinanc, D.
- Venue
- 2013 International Conference on Collaboration Technologies and Systems (CTS)
- Publisher
- IEEE
- Published
- 2013-05
- Pages
- 42-47
- OpenAlex
- W2131715540
- Cited by
- 1,296
- References
- 1
- FWCI
- 117.89
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
