Information Technology for the Data Integration in Intelligent Systems of Business Analytics

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Author(s)

Victoria Vysotska 1 Andrii Berko 1 Yevhen Burov 1 Dmytro Uhryn 2,* Zhengbing Hu 3 Valentyna Dvorzhak 2

1. Lviv Polytechnic National University/Information Systems and Networks Department, Lviv, 79013, Ukraine

2. Yuriy Fedkovich Chernivtsi National University/Computer Science Department, Chernivtsi, 58002, Ukraine

3. Hubei University of Technology/School of Computer Science, Wuhan, 430106, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2024.04.05

Received: 6 Mar. 2024 / Revised: 25 Apr. 2024 / Accepted: 11 Jun. 2024 / Published: 8 Aug. 2024

Index Terms

business analytics, data integration, information technologies, natural language processing, content analysis, information resources, intelligent system

Abstract

The purpose of the research is to develop mathematical models, solution methods and layouts of tools for problems solving of integrating information resources and creation of intelligent systems of business analytics based on effective models. These problems can be solved by automating the business processes execution and introducing artificial intelligence components into the business processes management systems. It can be said that the essence of the modern stage of the business processes modelling systems development is the transition from mainly manual (or with the use of auxiliary software) methods of business processes analysis to mainly automatic management of the business processes execution, construction of intelligent business processes networks in the interconnected conceptual models’ set form that encapsulate knowledge about the structure, the business processes features, system events, limitations and dependencies and are processed by machine. Decision-making powers are delegated to such information system in clearly defined (most often simple, routine) situations. So, in this way, it is possible to form the information resource of intelligent systems of business analytics as a single coherent set of data, suitable for use in solving a wide range of multifaceted problems. The integration approach of forming information resources has certain advantages over other approaches, in particular, regarding the information resources of intelligent systems of business analytics. The use of integration as a means of forming a set of consistent data has certain advantages, namely, it allows: combine data of different formats, content and origins in a single, consistent set; combine data without converting them to a single format, which is especially important when such conversion is difficult or impossible; creates virtual custom images of data that do not depend on their real appearance; creates opportunities to operate both real physical and virtual data in their combination; dynamically supplement, change and transform both the data itself and their descriptions; to provide uniform methods and technologies of perception and application of a large amount of various data.

Cite This Paper

Victoria Vysotska, Andrii Berko, Yevhen Burov, Dmytro Uhryn, Zhengbing Hu, Valentyna Dvorzhak, "Information Technology for the Data Integration in Intelligent Systems of Business Analytics", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.16, No.4, pp. 66-92, 2024. DOI:10.5815/ijieeb.2024.04.05

Reference

[1]V. Vysotska, “Analytical Method for Social Network User Profile Textual Content Monitoring Based on the Key Performance Indicators of the Web Page and Posts Analysis,” CEUR Workshop Proceedings, Vol. 3171, 2022, pp. 1380–1402.
[2]A. Osterwalder, “The business model ontology a proposition in a design science approach, Doctoral dissertation, Université de Lausanne, Faculté des hautes études commerciales, 2004.
[3]H. E. Eriksson, and M. Penker, “Business modeling with UML,” New York, 12. https://www.utm.mx/~caff/poo2/Business%20Modeling%20with%20UML.pdf
[4]T. H. Davenport, and J. E. Short, “The new industrial engineering: Information technology and business process redesign,” Operations management: Critical perspectives on business and management, 2003, pp. 97–123.
[5]T. H. Davenport, Process innovation: reengineering work through information technology, Harvard Business Press, 1993.
[6]M. Weske, “Concepts, languages, architectures,” Business Process Management, 2007.  DOI: 10.1007/978-3-642-28616-2.
[7]S. Russell, “ISO 9000: 2000 and the EFQM excellence model: competition or co-operation?,”Total quality management, Vol. 11(4-6), 2000, pp. 657–665. DOI: 10.1080/09544120050008039.
[8]P. Sampaio, P. Saraiva, and A. Guimarães Rodrigues, “ISO 9001 certification research: questions, answers and approaches,” International Journal of Quality & Reliability Management, Vol. 26(1), 2009, pp. 38–58. DOI: 10.1108/02656710910924161.
[9]B. B. Graham, Detail process charting: speaking the language of process, John Wiley & Sons, 2004.
[10]Why UML Fails to Add Value to the Design and Development Process Learning Lisp. http://lispy.wordpress.com/2008/10/29/why-uml-fails-to-add-value-to-the-design-and-development-process/
[11]B. Henderson-Sellers, and C. Gonzalez-Perez, “Uses and abuses of the stereotype mechanism in UML 1. x and 2.0,” International Conference on Model Driven Engineering Languages and Systems, Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 16–26, October 2006. DOI: 10.1007/11880240_2.
[12]M. Owen, and J. Raj, “BPMN and business process management,” Introduction to the new business process modeling standard, 2003, pp. 1–27. 
[13]Omg systems modeling language (omg sysml™), v1.0, Object Management Group, http://www.omg.org/spec/SysML/1.0/PDF
[14]J. Bolie, et.al. BPEL Cookbook: Best Practices for SOA-based integration and composite applications development, Packt Publishing, 2006.
[15]C. Howson, Business Objects XI: the complete referenceŠ± C McGraw-Hill, 2006.
[16]B. Larson, Delivering business intelligence with microsoft SQL server, McGraw-Hill, Inc., 2006.
[17]R. Davis, ARIS design platform: advanced process modelling and administration, Springer Science & Business Media, 2008.
[18]I. D. Lestantri, N. B. Janom, R. S. Aris, and Y. Husni, “The perceptions towards the digital sharing economy among SMEs: Preliminary findings,” Procedia Computer Science, Vol. 197, 2022, pp. 82–91.  DOI: 10.1016/j.procs.2021.12.121. 
[19]M. Bublyk, V. Vysotska, L. Chyrun, V. Panasyuk, and O. Brodyak, “Assessing Security Risks Method in E-Commerce System for IT Portfolio Management,” CEUR Workshop Proceedings, Vol. 2853, 2021, pp. 462-479.
[20]Y. Matseliukh, V. Vysotska, M. Bublyk, T. Kopach, and O. Korolenko, “Network Modelling of Resource Consumption Intensities in Human Capital Management in Digital Business Enterprises by the Critical Path Method,” CEUR Workshop Proceedings, Vol. 2851, 2021, pp. 366–380.
[21]D. M. Steiger, “Decision support as knowledge creation: A business intelligence design theory,” International Journal of Business Intelligence Research (IJBIR), Vol. 1(1), 2010, pp. 29-47.  DOI: 10.4018/jbir.2010071703.
[22]T. Lehmann, and A. Karcher, (). Ontology enabled decision support and situational awareness,” Intelligent Decision Technologies, Vol. 2(1), 2008, pp. 21–31.  DOI: 10.3233/IDT-2008-2103.
[23]L. Niu, J. Lu, and G. Zhang, “Cognition-driven decision support for business intelligence,” Models, Techniques, Systems and Applications. Studies in Computational Intelligence, Springer, Berlin, 2009, pp. 4–5. DOI: 10.1007/978-3-642-03208-0.
[24]V. Vysotska, O. Markiv, S. Tchynetskyi, B. Polishchuk, O. Bratasyuk, and V. Panasyuk, “Sentiment Analysis of Information Space as Feedback of Target Audience for Regional E-Business Support in Ukraine,” CEUR Workshop Proceedings, Vol. 3426, 2023, pp. 488–513.
[25]V. Vysotska, Y. Burov, L. Chyrun, S. Chyrun, O. Brodyak, V. Panasyuk, D. Karpyn, L. Pohreliuk, and N. Shykh “Knowledge presentation methods development in the intelligent business analytics systems based on ontologies and models,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 368-403.
[26]O. Cherednichenko, and F. Muhammad, “Collaborative Business Intelligence Virtual Assistant,” CEUR Workshop Proceedings, Vol. 3426, 2023, pp. 136–149.
[27]O. Cherednichenko, F. Muhammad, J. Darmont, and C. Favre, “Reference Model for Collaborative Business Intelligence Virtual Assistant,” CEUR Workshop Proceedings, Vol. 3403, 2023, pp. 114–125.
[28]R. Yurynets, Z. Yurynets, J. Becker, and O. Kryven, “Assessing Flexibility of Organizations for Strategic Development of Agricultural Business Projects,” CEUR Workshop Proceedings, Vol. 3387, 2023, pp. 289–299.
[29]R. Yurynets, Z. Yurynets, M. Nehrey, Y. Biriukova, and N. Zhyhaylo, “Modelling of Development of Hotel Business Potential and Economic Growth in Ukraine,” CEUR Workshop Proceedings, Vol. 3426, 2023, pp. 150-160.
[30]L. Chyrun, V. Andrunyk, L. Chyrun, A. Berko, I. Dyyak, and N. Antonyuk, “Online Business Processes Support Methods,” IEEE Proceedings of the 15th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT, 2020, 1, pp. 125–133.
[31]R. Yurynets, Z. Yurynets, I. Myshchyshyn, N. Zhyhaylo, and A. Pekhnyk, “Optimal Strategy for the Development of Insurance Business Structures in a Competitive Environment,” CEUR Workshop Proceedings, Vol. 2631, 2020, pp. 79–94.
[32]A. Kopp, and D. Orlovskyi, “Towards the Software Solution for Complexity Minimization of Business Process Models to Improve Understandability,” CEUR Workshop Proceedings, Vol-3426, 2023, pp. 274–286.
[33]A. Kopp, D. Orlovskyi, and S. Orekhov, “Towards Understandability Evaluation of Business Process Models using Activity Textual Analysis,” CEUR Workshop Proceedings, Vol-3312, 2022, pp. 200–211.
[34]A. Kopp, and D. Orlovskyi, “An Approach and a Software Tool for Automatic Source Code Generation driven by Business Rules,” CEUR Workshop Proceedings, Vol-3171, 2022, pp. 338–353.
[35]A. Kopp, and D. Orlovskyi, “Computational Technology and Software Tool for Translation of Business Rules into Database Creation Scripts,” CEUR Workshop Proceedings, Vol-3396, 2023, pp. 531–545.
[36]A. Berko, “Consolidated data models for electronic business systems,” The Experience of Designing and Application of CAD Systems in Microelectronics, CADSM, 2007, pp. 341–342.
[37]A.Y. Berko, “Methods and models of data integration in E-business systems,” Actual Problems of Economics, Vol. 10, 2008, pp. 17-24.
[38]N. Slyusarenko, O. Vlasenko, T. Gryshchenko, I. Novoseletska, V. Shakhrai, N. Stanislavchuk, O. Yakymchuk, “Professional competence building of the entrepreneurs through improving the quality of business education,” International Journal of Entrepreneurship, Vol. 25(7), 2021.
[39]O. Veres, P. Ilchuk, and O. Kots, “Big Data Analysis on the Enterprises’ Business Activity Under the COVID-19 Conditions,” CEUR Workshop Proceedings, Vol-3403, 2023, pp. 362–374.
[40]O. Veres, P. Ilchuk, and O. Kots, “The Concept of Using Artificial Intelligence Methods in Debt Financing of Business Entities,” CEUR Workshop Proceedings, Vol-3171, 2022, pp. 1542–1556.
[41]S. Albota, Z. Kunch, L. Kharchuk, and M. Hnatyuk, “Corpus research of semantic transformations of deterministic lexicon using the example of the lexeme virus,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 425-456.
[42]V. Vysotska, A. Berko, L. Chyrun, S. Chyrun, V. Panasyuk, I. Budz, I. Shakleina, O. Garbich-Moshora, I. Andrusyak, “Semantic data integration methods based on ontologies in intelligent business analytics systems,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 457-489.
[43]V. Teslyuk, I. Khomytska, I. Bazylevych, V. Holtvian, and O. Durytska, “The chi-square test and the Student’s t-test used for authorial style characterization,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 88-100.
[44]S. Dolgikh, “Unsupervised semantic analysis and zero-shot learning of newsgroup topics,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 1-12.
[45]V. Vysotska, “Linguistic intellectual analysis methods for Ukrainian textual content processing,” CEUR Workshop Proceedings, Vol. 3722, 2021, pp. 490-552.
[46]Morozov, V. V., Kalnichenko, O. V., & Mezentseva, O. O. O. M. (2020). The Method of Interation Modeling on Basis of Deep Learning the Neural Networks in Complex IT-Project. International Journal of Computing, 19(1), 88-96. 
[47]Marakhimov, A. R., & Khudaybergenov, K. K. (2020). Approach to the Synthesis of Neural Network Structure During Classification. International Journal of Computing, 19(1), 20-26.