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Data-Oriented Method to Big Data Standard System Creation: A Case of Chinese Financial Industry

Data-Oriented Method to Big Data Standard System Creation: A Case of Chinese Financial Industry Even though Big Data is a hot technology in the ICT industry with a large effect on economy and society, Big Data is a relatively indefinite concept, like a “laundry list”,compared with cloud computing and Internet of things. Fortunately, there is a consensus that Big Data standardization can promote the exchange and scoping of data, guarantee the data completeness and timeliness, ensure the quality of further analysis, eliminate information islands and improve the industry efficiency. However, the existed methods to Big Data standard system are all technology-oriented. This paper proposes an integrated method, called data-oriented method, which combines bottom–up, top–down, method of expertise with investigation together, to build Big Data standard system based on the data essence in the special field. This approach makes the system get rid of pure technique thinking and adapt more to practical condition. Meanwhile, this research also gives a case study on Chinese financial industry in practice. According to that this data-oriented method sets a close and accurate links between special data and standard system, it can be applied on the construction of Big Data standard system in other fields with improving the system model and laying a good foundation for Big Data applications and creations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

Data-Oriented Method to Big Data Standard System Creation: A Case of Chinese Financial Industry

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Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer-Verlag Berlin Heidelberg
Subject
Economics / Management Science; Business/Management Science, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Computing Methodologies
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-014-0024-6
Publisher site
See Article on Publisher Site

Abstract

Even though Big Data is a hot technology in the ICT industry with a large effect on economy and society, Big Data is a relatively indefinite concept, like a “laundry list”,compared with cloud computing and Internet of things. Fortunately, there is a consensus that Big Data standardization can promote the exchange and scoping of data, guarantee the data completeness and timeliness, ensure the quality of further analysis, eliminate information islands and improve the industry efficiency. However, the existed methods to Big Data standard system are all technology-oriented. This paper proposes an integrated method, called data-oriented method, which combines bottom–up, top–down, method of expertise with investigation together, to build Big Data standard system based on the data essence in the special field. This approach makes the system get rid of pure technique thinking and adapt more to practical condition. Meanwhile, this research also gives a case study on Chinese financial industry in practice. According to that this data-oriented method sets a close and accurate links between special data and standard system, it can be applied on the construction of Big Data standard system in other fields with improving the system model and laying a good foundation for Big Data applications and creations.

Journal

Annals of Data Science – Springer Journals

Published: Jan 9, 2015

References

  • Management information system for the information age
    Haag, S; Cumming, M
  • The new financial order: risks in the 21st century
    Robert, J
  • Big data: history, reality and future[M]
    Xu, ZP
  • The fourth paradigm: data-intensive scientific discovery
    Hey, T; Tansley, S; Tolle, K
  • Data assimilation: the ensemble Kalman filter
    Evenson, G
  • F.UNEP/world bank expert meeting on environmental accounting and the SNA
    Anthony, M
  • Design of a construction management data visualization environment: a top-down approach
    Chiu, C; Russell, AD
  • A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud
    Zhang, XY; Liu, C; Nepal, S
  • Sustainability assessment of U.S. final consumption and investments: triple-bottom-line input-output analysis
    Murat, K; Gokhan, E; Omer, T
  • Framework formation of financial data classification standard in the era of the big data
    Yang, S; Guo, K; Li, JP
  • Investments and portfolio management
    Zvi, B; Alex, K; Alan, JM
  • An epistemic framework for privacy protection in database linking
    Wang, DW; Liau, CJ; Hsu, TS
  • Big data analytics: turning big data into big money
    Ohlhorst, FJ