research-article

Big Data with Ten Big Characteristics

Authors:

Kenneth Strang,

Rongping LiAuthors Info & Claims

ICBDR '18: Proceedings of the 2nd International Conference on Big Data Research

Pages 56 - 61

https://doi.org/10.1145/3291801.3291822

Published: 27 October 2018 Publication History

Abstract

This paper reveals ten big characteristics (10 Bigs) of big data and explores their non-linear interrelationships through presenting a unified framework of big data. The framework has three levels: fundamental level, technological level, and socio-economic level. The fundamental level has four big fundamental characteristics of big data. The technological level consists of three big technological characteristics of big data. The socioeconomic level has three big socioeconomic characteristics of big data. The paper looks at each level of the proposed framework from a service-oriented perspective. The proposed approach in this paper might facilitate the research and development of big data, big data analytics, business intelligence, and business analytics.

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https://doi.org/10.62273/QNDU3179
Guo HLiang D(2024)The origin and research progress of Big Earth DataChinese Science Bulletin10.1360/TB-2023-055169:1(58-67)Online publication date: 5-Jan-2024
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Index Terms

Big Data with Ten Big Characteristics
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Business intelligence
  2. Information systems applications
    1. Decision support systems
      1. Data analytics

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ICBDR '18: Proceedings of the 2nd International Conference on Big Data Research

October 2018

221 pages

ISBN:9781450364768

DOI:10.1145/3291801

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shandong Univ.: Shandong University
University of Queensland: University of Queensland
Dalian Maritime University

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Association for Computing Machinery

New York, NY, United States

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Published: 27 October 2018

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ICBDR 2018: 2018 The 2nd International Conference on Big Data Research

October 27 - 29, 2018

Weihai, China

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Cited By

Mohammed ALind M(2024)Examining Factors Influencing the Acceptance of Big Data Analytics in HealthcareJournal of Information Systems Applied Research10.62273/QNDU317917:2(31-44)Online publication date: 2024
https://doi.org/10.62273/QNDU3179
Guo HLiang D(2024)The origin and research progress of Big Earth DataChinese Science Bulletin10.1360/TB-2023-055169:1(58-67)Online publication date: 5-Jan-2024
https://doi.org/10.1360/TB-2023-0551
T DKhamesra NBhargavi M(2024)Driving Sustainability using Big Data Analytics2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)10.1109/ICETSIS61505.2024.10459428(258-262)Online publication date: 28-Jan-2024
https://doi.org/10.1109/ICETSIS61505.2024.10459428
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https://doi.org/10.1080/07366981.2024.2376791
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