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Data Mining Approach Improving Decision-Making Competency Along the Business Digital Transformation Journey: A Literature Review

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Emerging Technologies in Computing (iCETiC 2021)

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Abstract

Advanced analytics and artificial intelligence are drivers of deep analysis and change in the perspective of businesses’ digital transformation. Data mining, as an essential part of artificial intelligence, is a powerful digital technology, which provides guidance for businesses in terms of analyzing information and predicting in business. The key advantage of the application of the data mining approach in business is the impact by improving customers’ experience and decision-making. The aim of this research is to present a theoretical model to understand the researchers’ perspectives on data mining application in different business areas and digital transformation, and the discussion of some benefits and challenges of the data mining application in improving decision-making along the digital transformation of businesses. Moreover, this paper analyzes how the implementation of data mining techniques in business can lead to an increased efficiency and business productivity along their digital transformation journey.

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Authors and Affiliations

  1. CST Faculty, South-East European University, Tetovo, Republic of Macedonia

    Hyrmet Mydyti & Arbana Kadriu

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  1. Hyrmet Mydyti
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  2. Arbana Kadriu
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Correspondence to Hyrmet Mydyti .

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Editors and Affiliations

  1. Xiamen University Malaysia, Sepang, Malaysia

    Mahdi H. Miraz

  2. University of Chester, Chester, UK

    Garfield Southall

  3. Epoka University, Tiranë, Albania

    Maaruf Ali

  4. University of South Wales, Pontypridd, Mid Glamorgan, UK

    Andrew Ware

  5. University of Fairfax, Fairfax, VA, USA

    Safeeullah Soomro

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Mydyti, H., Kadriu, A. (2021). Data Mining Approach Improving Decision-Making Competency Along the Business Digital Transformation Journey: A Literature Review. In: Miraz, M.H., Southall, G., Ali, M., Ware, A., Soomro, S. (eds) Emerging Technologies in Computing. iCETiC 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 395. Springer, Cham. https://doi.org/10.1007/978-3-030-90016-8_9

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