The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Big data with cloud computing: Discussions and challenges
Open accessAbstract
With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, Amazon Web Services, International Business Machine cloud, Hortonworks, and MapR. A comparative analysis of various cloud-based big data frameworks is also performed. Various research challenges are defined in terms of distributed database storage, data security, heterogeneity, and data visualization.
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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
The rise of big data on cloud computing: Review and open research issues
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Big data, smart cities and city planning
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A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis
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Big Data technologies: A survey
Oussous, A., Benjelloun, F.-Z., Ait Lahcen, A., & Belfkih, S. (2018) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2017.06.001 · Cited by 980
Big data: Issues, challenges, tools and Good practices
Katal, A., Wazid, M., & Goudar, R. H. (2013) · 2013 Sixth International Conference on Contemporary Computing (IC3) · doi:10.1109/ic3.2013.6612229 · Cited by 862
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‘Big data’, Hadoop and cloud computing in genomics
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Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics
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Cited by
Data Quality Management in Big Data: Strategies, Tools, and Educational Implications
Nguyen, T., Nguyen, H.-T., & Nguyen-Hoang, T.-A. (2025) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2025.105067 · Cited by 20
Metadata
- Authors
- Sandhu, A. K.
- Venue
- Big Data Mining and Analytics
- Publisher
- Tsinghua University Press
- Published
- 2022-03
- Volume
- 5
- Issue
- 1
- Pages
- 32-40
- ISSN
- 2096-0654 (ISSN-L)
- 2097-406X
- OpenAlex
- W4281660018
- Cited by
- 280
- References
- 29
- FWCI
- 62.26
- Type
- journal article
- Language
- en
- Open access
- diamond
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
