Autors: Ilieva, R. Y., Ivanova, M. S., Peycheva, T. P., Nikolov, Y. P.
Title: Modelling in support of decision making in Business Intelligence
Keywords: Business Intelligence, Artificial Intelligence, Machine Lear

Abstract: Modelling in support of decision making in business intelligence (BI) starts with exploring the BI systems, driven by artificial intelligence (AI). The purpose why AI will be the core of next generation analytics and why BI will be empowered by IT are determined. The role of AI and machine learning (ML) in business processes automation is analyzed. The benefits from AI integration in BI platforms are summarized. Then analysis goes through predictive modeling in the domain of e-commerce. The use of ML for predictive modeling is overviewed. Construction of predictive and clustering models is proposed. After that the importance of self-services in BI platforms is outlined. In this context the self-service BI is defined and what are the key steps to create successful self-service BI model are sketched. The effects of potential threads which are the results of the big data in the business world are examined and some suggestions for the future have been made. Lastly game-changer trends in BI



    Integration Challenges for Analytics, Business Intelligence, and Data Mining, pp. 115-145, 2021, United States, IGI Global eEditorial Discovery®, DOI: 10.4018/978-1-7998-5781-5

    Цитирания (Citation/s):
    1. Neethirajan, Suresh, and Bas Kemp. "Digital twins in livestock farming." Animals 11.4 (2021): 1008. - 2021 - в издания, индексирани в Scopus или Web of Science
    2. Neethirajan, S., and B. Kemp. "Digital Phenotyping in Livestock Farming. Animals 2021, 11, 2009." (2021). - 2021 - в издания, индексирани в Scopus или Web of Science
    3. Yi Xu, Xiaojuan Li, Fajaruddin bin Mustakim, Fahad M. Alotaibi, Nabaz Nawzad Abdullah, Investigating the business intelligence capabilities’ and network learning effect on the data mining for start-up's function, Information Processing & Management, Volume 59, Issue 5, 2022, 103055, ISSN 0306-4573, ( - 2022 - в издания, индексирани в Scopus или Web of Science
    4. M. E. Fedosovsky, M. M. Uvarov, S. A. Aleksanin, A. A. Pyrkin, A. W. Colombo and D. Prattichizzo, "Sustainable Hyperautomation in High-Tech Manufacturing Industries: A Case of Linear Electromechanical Actuators," in IEEE Access, vol. 10, pp. 98204-98219, 2022, doi: 10.1109/ACCESS.2022.3205623. - 2022 - в издания, индексирани в Scopus или Web of Science

    Вид: книга/глава(и) от книга, публикация в реферирано издание, индексирана в Scopus