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Systematic Literature Review of Big Data Analytics

Published:21 June 2017Publication History

ABSTRACT

This paper aims to identify some emerging sectors that apply big-data analytics through a systematic literature review conducted by capturing the existing work done in this subject area by academicians and industry experts worldwide and specifically in India backed by a detailed domain-wise, nation-wise and within India, an institute-wise analysis of the contributions made. Based on the existing work, the need for applying analytics in Banking and Finance is emphasized through the paper and a premise is provided for conducting future research in this domain.

References

  1. Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36, 700--710. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Das.S.(2016)."How Indian brokers use analytics to predict the stock market". The CIO. Retrieved from: http://www.cio.in/feature/how-indian-brokers-use-analytics-predict-stock-market.Google ScholarGoogle Scholar

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  1. Systematic Literature Review of Big Data Analytics

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    • Published in

      cover image ACM Conferences
      SIGMIS-CPR '17: Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research
      June 2017
      220 pages
      ISBN:9781450350372
      DOI:10.1145/3084381

      Copyright © 2017 Owner/Author

      Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 21 June 2017

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      Overall Acceptance Rate300of480submissions,63%

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