Research on Business Intelligence with Data Mining Applications

Jason C. H. Chen; Napoleone Piani

doi:doi:10.11648/j.ijber.20170602.11

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Research on Business Intelligence with Data Mining Applications

Jason C. H. Chen, Napoleone Piani

Published in International Journal of Business and Economics Research (Volume 6, Issue 2)

Received: 21 April 2017 Accepted: Published: 21 April 2017

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Abstract

Business Intelligence (BI) has become an important agenda for many top executives because they have become extremely aware of its value in providing a competitive differentiator at all levels of the organizations. This paper discusses the concepts and technologies of business intelligence, specially, data warehousing and data mining and how these can positively influence and benefit a business. Review on BI frameworks and research models for developing data warehousing and data mining are presented and analyzed. The paper also illustrates a business scenario in which the Rapidminer, a data mining tool can be used to extrapolate relevant data to a small startup ski shop.

Published in	International Journal of Business and Economics Research (Volume 6, Issue 2)
DOI	10.11648/j.ijber.20170602.11
Page(s)	19-24
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), 2024. Published by Science Publishing Group

Keywords

business intelligence (BI), data mining, rapidminer

References

[1]	Berbel R. L. T. and Gonzalez S. SM (2015). “How to help end users to get better decisions” Personalising OLAP aggregation queries through semantic recommendation of text documents, International Journal of Business Intelligence and Data mining, Vol. 10, No. 1.
[2]	Biere, Mike (2010). The New Era of Enterprise Business Intelligence, IBM Press.
[3]	Chaudhuri, Surajit; Dayal, Umeshwar; Narasayya, Vivek (2011). "An Overview of Business Intelligence Technology", Communications of the ACM 54.8 pp. 88-98.
[4]	Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer-Verlag.
[5]	Hoffer, J. A., Topi, H. and Ramesh, V. (2014). Essentials of Data Management, Pearson.
[6]	Kroenke, D. M. and Boyle, R. J. (2017). Using MIS, Pearson.
[7]	North, Matthew (2012). Data Mining for the Masses, A Global Text Project Book.
[8]	Rahman M. M., Maksud, U. A. and Rahman, S. M. M. (2015). “An open multi-tier architecture for high-performance data mining using SOA,” International Journal of Data Mining, Modelling and Management, Vol. 7, No. 1.
[9]	StatSoft.com (2004), available at https://www.statsoft.com/Portals/0/Customers/Success_Stories/argonauten360.pdf.
[10]	Stock, Tom. (2011). "Using a Data Warehouse to Solve Risk, Performance, Reporting and Compliance-Related Issues," Journal of Securities Operations & Custody 3.4, pp. 305-315.
[11]	Turban, E., Sharda R. and Delen D. (2014). “Business Intelligence: A Managerial Approach”, Prentice-Hall, 3^rd Edition.
[12]	Victor, N. and Lopez, D. (2016). “Privacy models for big data: a survey”, International Journal of Big Data Intelligence, Vol. 3, No. 1.
[13]	Wikipedia.a (2017), available at: https://en.wikipedia.org/wiki/Ken_Olsen.
[14]	Wikipedia.b (2017), available at: https://en.wikipedia.org/wiki/Hartsfield%E2%80%93Jackson_Atlanta_International_Airport.

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Jason C. H. Chen, Napoleone Piani. (2017). Research on Business Intelligence with Data Mining Applications. International Journal of Business and Economics Research, 6(2), 19-24. https://doi.org/10.11648/j.ijber.20170602.11

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ACS Style

Jason C. H. Chen; Napoleone Piani. Research on Business Intelligence with Data Mining Applications. Int. J. Bus. Econ. Res. 2017, 6(2), 19-24. doi: 10.11648/j.ijber.20170602.11

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AMA Style

Jason C. H. Chen, Napoleone Piani. Research on Business Intelligence with Data Mining Applications. Int J Bus Econ Res. 2017;6(2):19-24. doi: 10.11648/j.ijber.20170602.11

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@article{10.11648/j.ijber.20170602.11,
  author = {Jason C. H. Chen and Napoleone Piani},
  title = {Research on Business Intelligence with Data Mining Applications},
  journal = {International Journal of Business and Economics Research},
  volume = {6},
  number = {2},
  pages = {19-24},
  doi = {10.11648/j.ijber.20170602.11},
  url = {https://doi.org/10.11648/j.ijber.20170602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20170602.11},
  abstract = {Business Intelligence (BI) has become an important agenda for many top executives because they have become extremely aware of its value in providing a competitive differentiator at all levels of the organizations. This paper discusses the concepts and technologies of business intelligence, specially, data warehousing and data mining and how these can positively influence and benefit a business. Review on BI frameworks and research models for developing data warehousing and data mining are presented and analyzed. The paper also illustrates a business scenario in which the Rapidminer, a data mining tool can be used to extrapolate relevant data to a small startup ski shop.},
 year = {2017}
}

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TY  - JOUR
T1  - Research on Business Intelligence with Data Mining Applications
AU  - Jason C. H. Chen
AU  - Napoleone Piani
Y1  - 2017/04/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ijber.20170602.11
DO  - 10.11648/j.ijber.20170602.11
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 19
EP  - 24
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20170602.11
AB  - Business Intelligence (BI) has become an important agenda for many top executives because they have become extremely aware of its value in providing a competitive differentiator at all levels of the organizations. This paper discusses the concepts and technologies of business intelligence, specially, data warehousing and data mining and how these can positively influence and benefit a business. Review on BI frameworks and research models for developing data warehousing and data mining are presented and analyzed. The paper also illustrates a business scenario in which the Rapidminer, a data mining tool can be used to extrapolate relevant data to a small startup ski shop.
VL  - 6
IS  - 2
ER  -

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Author Information

Jason C. H. Chen

School of Business Administration, Gonzaga University, Spokane, USA
Napoleone Piani

School of Business Administration, Gonzaga University, Spokane, USA

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APA Style

Jason C. H. Chen, Napoleone Piani. (2017). Research on Business Intelligence with Data Mining Applications. International Journal of Business and Economics Research, 6(2), 19-24. https://doi.org/10.11648/j.ijber.20170602.11

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ACS Style

Jason C. H. Chen; Napoleone Piani. Research on Business Intelligence with Data Mining Applications. Int. J. Bus. Econ. Res. 2017, 6(2), 19-24. doi: 10.11648/j.ijber.20170602.11

Copy | Download

AMA Style

Jason C. H. Chen, Napoleone Piani. Research on Business Intelligence with Data Mining Applications. Int J Bus Econ Res. 2017;6(2):19-24. doi: 10.11648/j.ijber.20170602.11

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@article{10.11648/j.ijber.20170602.11,
  author = {Jason C. H. Chen and Napoleone Piani},
  title = {Research on Business Intelligence with Data Mining Applications},
  journal = {International Journal of Business and Economics Research},
  volume = {6},
  number = {2},
  pages = {19-24},
  doi = {10.11648/j.ijber.20170602.11},
  url = {https://doi.org/10.11648/j.ijber.20170602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20170602.11},
  abstract = {Business Intelligence (BI) has become an important agenda for many top executives because they have become extremely aware of its value in providing a competitive differentiator at all levels of the organizations. This paper discusses the concepts and technologies of business intelligence, specially, data warehousing and data mining and how these can positively influence and benefit a business. Review on BI frameworks and research models for developing data warehousing and data mining are presented and analyzed. The paper also illustrates a business scenario in which the Rapidminer, a data mining tool can be used to extrapolate relevant data to a small startup ski shop.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Research on Business Intelligence with Data Mining Applications
AU  - Jason C. H. Chen
AU  - Napoleone Piani
Y1  - 2017/04/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ijber.20170602.11
DO  - 10.11648/j.ijber.20170602.11
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 19
EP  - 24
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20170602.11
AB  - Business Intelligence (BI) has become an important agenda for many top executives because they have become extremely aware of its value in providing a competitive differentiator at all levels of the organizations. This paper discusses the concepts and technologies of business intelligence, specially, data warehousing and data mining and how these can positively influence and benefit a business. Review on BI frameworks and research models for developing data warehousing and data mining are presented and analyzed. The paper also illustrates a business scenario in which the Rapidminer, a data mining tool can be used to extrapolate relevant data to a small startup ski shop.
VL  - 6
IS  - 2
ER  -

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