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Reviewing Data Mining as an enabling technology for BI

Author

Listed:
  • Mustafa Nizamul Aziz

    (Senior Lecturer, East West University, Dhaka, Bangladesh.)

  • A.K.M. Monzurul Islam

    (Independent University, Bangladesh.)

Abstract

Data mining (DM) is the process of discovering or “mining” new knowledge from large databases and applying it to decision making. In recent times, companies have been using a wide range of data mining techniques to better understand their customers and their performance and solve complex business problems. Data mining is a way to develop Business Intelligence (BI) from data that an organization collects, organizes, and stores. The purpose of this paper is to review Data Mining as an enabling technology for Business Intelligence. Documents analysis was used as the data collection method and a qualitative approach was used for data analysis in the study.

Suggested Citation

  • Mustafa Nizamul Aziz & A.K.M. Monzurul Islam, 2020. "Reviewing Data Mining as an enabling technology for BI," International Journal of Science and Business, IJSAB International, vol. 4(7), pages 46-51.
    • Handle: RePEc:aif:journl:v:4:y:2020:i:7:p:46-51
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    References listed on IDEAS

    as
    1. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
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    Cited by:

    1. Chnar Mustaf Mohammed & Shavan Askar, 2021. "Machine Learning for IoT HealthCare Applications: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 42-51.
    2. Shavan Askar & Faris Keti, 2021. "Performance Evaluation of Different SDN Controllers," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 67-80.

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