ACS Applied Computer Science

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DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY

Jolanta BRZOZOWSKA, Jakub PIZOŃ, Gulzhan BAYTIKENOVA, Arkadiusz GOLA, Alfiya ZAKIMOVA, Katarzyna PIOTROWSKA
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The paper describes one of the methods of data acquisition in data mining models used to support decision-making. The study presents the possibilities of data collection using the phases of the CRISP-DM model for an organization and presents the possibility of adapting the model for analysis and management in the decision-making process. The first three phases of implementing the CRISP-DM model are described using data from an enterprise with small batch production as an example. The paper presents the CRISP-DM based model for data mining in the process of predicting assembly cycle time. The developed solution has been evaluated using real industrial data and will be a part of methodology that allows to estimate the assembly time of a finished product at the quotation stage, i.e., without the detailed technology of the product being known. 

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  • APA 7th style
Brzozowska, J., Pizoń, J., Baytikenova, G., Gola, A., Zakimova, A., & Piotrowska, K. (2023). Data engineering in CRISP-DM process  production data – case study. Applied Computer Science, 19(3), 83-95. https://doi.org/10.35784/acs-2023-26
  • Chicago style
Brzozowska, Jolanta, Jakub Pizoń,  Gulzhan Baytikenova, Arkadiusz Gola, Alfiya Zakimova, and Katarzyna Piotrowska. "Data engineering in CRISP-DM process  production data – case study." Applied Computer Science 19, no. 3 (2023): 83-95.
  • IEEE style
J. Brzozowska, J. Pizoń, G. Baytikenova, A. Gola, A. Zakimova, and K. Piotrowska, "Data engineering in CRISP-DM process  production data – case study," Applied Computer Science, vol. 19, no. 3, pp.83-95, 2023, doi: 10.35784/acs-2023-26.
  • Vancouver style
Brzozowska J, Pizoń J, Baytikenova G, Gola A, Zakimova A, Piotrowska K. Data engineering in CRISP-DM process  production data – case study. Applied Computer Science. 2023;19(3):83-95.

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