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Details

Autor(en) / Beteiligte
Titel
Cloud and Big Data: A Mutual Benefit for Organization Development
Ist Teil von
  • Journal of physics. Conference series, 2021-02, Vol.1767 (1), p.12020
Ort / Verlag
Bristol: IOP Publishing
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Electronic Journals Library - Freely accessible e-journals
Beschreibungen/Notizen
  • The emergence of big data as a novel model gives unparalleled composition and value for an organization. The growth of big data is posing challenges in areas such as processing, analytics, sharing, and visualization. Interestingly, the cloud computing technology also emanated to specify important required infrastructure to tackle these disputes. Cloud computing is an effective interface that's used to manipulate enormous-scale and complicated calculations. It eliminated the requirement to sustain lavish computing hardware, dedicated infrastructure, and software. Big data and cloud computing (BDCC) are considered to become the source of productivity that drives today's electronic business transformations. Nonetheless, the ratio of the companies that adopt and use BDCC isn't significant. There are also obstacles to facilitating BDCC's market proliferation. Hence, this paper aims to recognize and emphasize the factors that affect the adoption and use of BDCC in technology-organization-environment (TOE) viewpoints in enterprises. Data were obtained from a sample of 100 companies to scientifically check our system. The understanding of BDCC's potential advantages and technical capabilities are defined as the BDCC's important elements. Consistency with current infrastructure, data reliability and functionality, and protection and privacy are highly rated within the sense of technologies. Managerial expertise and financial expenditure capacity for the application and use of BDCC and governmental assistance and regulation are defined as organizational and environmental considerations for acceptance and use, simultaneously.
Sprache
Englisch
Identifikatoren
ISSN: 1742-6588
eISSN: 1742-6596
DOI: 10.1088/1742-6596/1767/1/012020
Titel-ID: cdi_iop_journals_10_1088_1742_6596_1767_1_012020

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