The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Big Data: Survey, Technologies, Opportunities, and Challenges
Open accessAbstract
Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
![Figure 1 Challenges in Big Data [13].](/paper-figures/c7f0ec3982ce41b595fed4c64e978675/big-data-survey-technologies-opportunities-and-challenges-figure-1.jpg)





Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Social media provides voluminous, varied and velocitous data of potential value to decision makers and is a rich source for big data [31].”
From A Big Data Analytics Method for Tourist Behaviour Analysis (2017) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Madden, S. (2012) · IEEE Internet Computing · doi:10.1109/mic.2012.50 · Cited by 509
Big data: the end of privacy or a new beginning?
Rubinstein, I. S. (2013) · International Data Privacy Law · doi:10.1093/idpl/ips036 · Cited by 257
Research works printed but not linked: 36
- 2013, From Big Data to Big Data Mining: challenges, issues, and opportunities, 1
- 10.1016/j.clsr.2013.07.007 · DOI
- 10.1126/science.1200970 · DOI · Paper page
- 10.1098/rsta.2008.0118 · DOI · Paper page
- 2012, Science, 336, 22, 10.1126/science.336.6077.22 · DOI
- 10.1007/978-3-642-39146-0_2 · DOI
- 10.1109/JPROC.2012.2189787 · DOI
- 2006, EE Times
- 2008, Nature, 455, 8, 10.1038/455008a · DOI
- 10.1016/j.proeng.2011.11.2539 · DOI
- 10.1093/comjnl/bxs074 · DOI
- 10.1016/j.jbi.2013.07.001 · DOI
- 2013, Journal of System and Network Engineering, 1
- Proceedings of World Academy of Science: Engineering & Technology, 48
- 10.1023/A:1021515408295 · DOI
- 10.1109/SURV.2011.060710.00066 · DOI
- 2012, Proceedings of the VLDB Endowment, 5, 2032, 10.14778/2367502.2367572 · DOI · Paper page
- 10.1016/j.addr.2013.04.008 · DOI
- 10.1109/MIS.2013.39 · DOI
- 2013, Editorial: IEEE Computer, 46, 22
- 10.1109/MC.2013.162 · DOI
- 10.1177/0165551513478738 · DOI
- 10.1016/j.cageo.2013.07.025 · DOI
- 2013, ACM SIGKDD Explorations Newsletter, 14, 6, 10.1145/2481244.2481247 · DOI
- 10.1007/s10115-007-0114-2 · DOI · Paper page
- 2010, The Journal of Machine Learning Research, 11, 1601
- 10.1007/978-3-642-40270-8_1 · DOI
- 10.1109/MC.2013.147 · DOI
- 2013, The Guardian
- 2013, Stanford Law Review Online, 66
- 2012, NYU School of Law, Public Law Research Paper, 12
- 10.1016/j.clsr.2009.02.002 · DOI · Paper page
- 10.1109/SURV.2012.060912.00182 · DOI
- 10.1109/MCSE.2011.77 · DOI
- 10.1109/MC.2003.1250885 · DOI
- 10.1109/MC.2009.26 · DOI
Cited by
Sorted by citations
The role of big data in smart city
Hashem, I. A. T., Chang, V., Anuar, N. B., Adewole, K., Yaqoob, I., Gani, A., Ahmed, E., & Chiroma, H. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.05.002 · Cited by 1,103
Self-citationSocial big data: recent achievements and new challenges
Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016) · Information Fusion · doi:10.1016/j.inffus.2015.08.005 · Cited by 846
Big data: From beginning to future
Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A. V. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.07.009 · Cited by 410
Self-citationData Science: A Comprehensive Overview
Cao, L. (2018) · ACM Computing Surveys · doi:10.1145/3076253 · Cited by 407
“A fundamental trigger for the above questions and many others not mentioned here is the exploration of new or more complex challenges and opportunities [Jagadish et al. 2014; Cao 2016b; 2010a; Khan et al. 2014] in data science and engineering.”
BackgroundA Big Data Analytics Method for Tourist Behaviour Analysis
Miah, S. J., Vu, H. Q., Gammack, J., & McGrath, M. (2017) · Information & Management · doi:10.1016/j.im.2016.11.011 · Cited by 393
Metadata
- Authors
- Khan, N., Yaqoob, I., Hashem, I. A. T., Inayat, Z., Mahmoud Ali, W. K., Alam, M., Shiraz, M., & Gani, A.
- Affiliations
- Abdul Wali Khan University Mardan (PK)
- University of Malaya (MY)
- Mobile Cloud Computing Research Lab, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia
- Saudi Electronic University (SA)
- Corresponding author
- Khan, Nawsher
- Venue
- The Scientific World Journal
- Publisher
- Wiley
- Published
- 2014
- Volume
- 2014
- Pages
- 1-18
- ISSN
- 1537-744X (ISSN-L)
- 2356-6140
- PMC
- PMC4127205
- OpenAlex
- W2000432868
- Cited by
- 547
- References
- 3
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 42 · 2023: 42 · 2022: 52 · 2021: 68 · 2020: 66 · 2019: 80 · 2018: 78 · 2017: 46 · 2016: 26 · 2015: 12 · 2014: 1
- FWCI
- 53.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- The Scientific World JOURNAL (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Charles Sturt University Research Output (CRO) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Greater South Information System
- Funders
- Ministry of Higher Education, Malaysia (UM.C/625/1/HIR/MOHE/FCSIT/03, RP012C-13AFR)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Information Systems › Big Data and Digital Economy
- Keywords
- big data, big data definition, data volume growth, data volume, big data management, big data analytics, data security, data lifecycle
- MeSH terms
- Electronic Data Processing, Information Storage and Retrieval, Internet, Access to Information, Information Dissemination
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review