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Creating New Types of Business and Economic Indicators Using Big Data Technologies

Received: 7 November 2014     Accepted: 29 November 2014     Published: 27 December 2014
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Abstract

Today, every business is a data business. Data is available from internal and external sources about transactions, processes, customers, competitors, trends, technological changes, etc. The challenge is to create actionable information and useful knowledge for the company. If companies are not leveraging their data assets, then competitors will outperform them. Big data technologies can provide a very efficient tool for the discovery of knowledge hidden in the company and its environment. Creating company specific indicators by analyzing large datasets can lead to valuable insights and better decisions. Big data technologies can also provide new and faster methods to calculate economic indicators (GDP figures, tax revenue forecasts, etc.). It can help the work of economic policy makers by reducing the latency of data that allows for timely intervention if necessary. It can also create new, not yet available information.

Published in Science Journal of Business and Management (Volume 3, Issue 1-1)

This article belongs to the Special Issue The Role of Knowledge and Management’s Tasks in the Companies

DOI 10.11648/j.sjbm.s.2015030101.14
Page(s) 18-24
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Indicators, Big Data, Business Analytics

References
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[11] IBM Business Analytics, “Business Analytics for Big Data: Unlock Value to Fuel Performance”, IBM Corporation, Software Group, June 2013, URL: http://www-01.ibm.com/software/analytics/solutions/big-data/ (September 30, 2014)
[12] B. Marr, “Big Data Is Nothing Without Its Little Brother”, Smart Data Collective Blog, March 18, 2014, URL: http://smartdatacollective.com/bernardmarr/191631/big-data-nothing-without-it-s-little-brother (September 19, 2014)
[13] IBM, “Global CFO Study 2010”, IBM Corporation, 2010, URL: http://www.ibm.com/services/us/cfo/cfostudy2010/ (May 5, 2014)
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[18] V. O. Sust, E. G. Illera, A. S. Berengué, R. G. García, M. V. P. Alonso, M. J. T. Torres, G. R. Verard, O. L. Albert, X. C. Ramos and P. R. Rodríguez, “Big Data And Tourism: New Indicators For Tourism Management”, RocaSalvatella and Telefónica, Barcelona, May 2014, URL: http://www.rocasalvatella.com/en/big-data-and-tourism-new-indicators-tourism-management-0 (September 19, 2014)
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[23] This work was supported by the European Union and the European Social Fund through FuturICT.hu project (grant no.: TAMOP-4.2.2.C-11/1/KONV-2012-0013). "
Cite This Article
  • APA Style

    Péter Szármes. (2014). Creating New Types of Business and Economic Indicators Using Big Data Technologies. Science Journal of Business and Management, 3(1-1), 18-24. https://doi.org/10.11648/j.sjbm.s.2015030101.14

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    ACS Style

    Péter Szármes. Creating New Types of Business and Economic Indicators Using Big Data Technologies. Sci. J. Bus. Manag. 2014, 3(1-1), 18-24. doi: 10.11648/j.sjbm.s.2015030101.14

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    AMA Style

    Péter Szármes. Creating New Types of Business and Economic Indicators Using Big Data Technologies. Sci J Bus Manag. 2014;3(1-1):18-24. doi: 10.11648/j.sjbm.s.2015030101.14

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  • @article{10.11648/j.sjbm.s.2015030101.14,
      author = {Péter Szármes},
      title = {Creating New Types of Business and Economic Indicators Using Big Data Technologies},
      journal = {Science Journal of Business and Management},
      volume = {3},
      number = {1-1},
      pages = {18-24},
      doi = {10.11648/j.sjbm.s.2015030101.14},
      url = {https://doi.org/10.11648/j.sjbm.s.2015030101.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.s.2015030101.14},
      abstract = {Today, every business is a data business. Data is available from internal and external sources about transactions, processes, customers, competitors, trends, technological changes, etc. The challenge is to create actionable information and useful knowledge for the company. If companies are not leveraging their data assets, then competitors will outperform them. Big data technologies can provide a very efficient tool for the discovery of knowledge hidden in the company and its environment. Creating company specific indicators by analyzing large datasets can lead to valuable insights and better decisions. Big data technologies can also provide new and faster methods to calculate economic indicators (GDP figures, tax revenue forecasts, etc.). It can help the work of economic policy makers by reducing the latency of data that allows for timely intervention if necessary. It can also create new, not yet available information.},
     year = {2014}
    }
    

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    AB  - Today, every business is a data business. Data is available from internal and external sources about transactions, processes, customers, competitors, trends, technological changes, etc. The challenge is to create actionable information and useful knowledge for the company. If companies are not leveraging their data assets, then competitors will outperform them. Big data technologies can provide a very efficient tool for the discovery of knowledge hidden in the company and its environment. Creating company specific indicators by analyzing large datasets can lead to valuable insights and better decisions. Big data technologies can also provide new and faster methods to calculate economic indicators (GDP figures, tax revenue forecasts, etc.). It can help the work of economic policy makers by reducing the latency of data that allows for timely intervention if necessary. It can also create new, not yet available information.
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Author Information
  • Multidisciplinary Doctoral School of Engineering Sciences, Széchenyi István University, Gy?r, Hungary

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