The rise of "big data" on cloud computing: Review and open research issues

By Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar, Abdullah Bin Gani, Samee Ullah Khan. Information Systems, 2015

2,605 citations recorded by the source corpus.

Subfields: Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2660dcf5bd16d14862a7bbb241fa4d85ae34327f

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In Information Systems

In Management Science and Operations Research

Citations in the corpus

Big Data Analytics in Operations Management (2018, background): “…a systematic review on the business value of big data (Wamba et al. 2015), a review on the role played by cloud computing in big data analytics (Hashem et al. 2015), an update of the development in big data analytics for business applications and risk analysis (Choi et al. 2017a), a taxonomy…”
Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics (2019, background): “Using cloud computing to build an IoT platform can reduce costs and achieve efficient calculation and storage [101].”
Big Data in Smart Farming – A review (2017, background): “Bigdatarequires a set of techniques and technologies with new forms of integration to reveal insights from datasets that arediverse, complex,andof a massive scale (Hashem et al., 2015).”
The role of big data in smart city (2016, methodology): “Cloud computing also provides the underlying engine via the big data technology such as Hadoop framework (Hashem et al., 2015).”
FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record (2018, background): “Traditionally, healthcare data distributed across sites centralized in a database for access for analysis [13, 8, 7].”
The dual effects of the Internet of Things (IoT): A systematic review of the benefits and risks of IoT adoption by organizations (2020, background): “As such, adopting IoT may provide a wide variety of benefits for organizations and the resulting big data offers the potential for organizations to obtain valuable insights (Dwivedi et al., 2017; Hashem et al., 2015).”
Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges (2017, methodology): “algorithms used in big data analysis, which is not rising linearly with the rapid increase in computational resources [19].”
Feature selection for high-dimensional data (2016, background): “Nowadays, value is considered themost important V because it refers to the process of discovering huge hiddenvalues from large data sets with various types and rapid generation [32].”
Big Data sources and methods for social and economic analyses (2017, background): “Con-cretely, the role of cloud computing as part of a Big Data system has been explored by Hashem et al. (2015).”