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Behbahani Nejad, M. R., Rashidi, H.. (1401). A Novel Architecture based on Business Intelligence Approach to Exploit Big Data. فناوری آموزش, 11(1), 85-102. doi: 10.22061/jecei.2022.8565.529
M. R. Behbahani Nejad; H. Rashidi. "A Novel Architecture based on Business Intelligence Approach to Exploit Big Data". فناوری آموزش, 11, 1, 1401, 85-102. doi: 10.22061/jecei.2022.8565.529
Behbahani Nejad, M. R., Rashidi, H.. (1401). 'A Novel Architecture based on Business Intelligence Approach to Exploit Big Data', فناوری آموزش, 11(1), pp. 85-102. doi: 10.22061/jecei.2022.8565.529
Behbahani Nejad, M. R., Rashidi, H.. A Novel Architecture based on Business Intelligence Approach to Exploit Big Data. فناوری آموزش, 1401; 11(1): 85-102. doi: 10.22061/jecei.2022.8565.529

A Novel Architecture based on Business Intelligence Approach to Exploit Big Data

Journal of Electrical and Computer Engineering Innovations (JECEI)
دوره 11، شماره 1، فروردین 2023، صفحه 85-102    اصل مقاله (1.17 M)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2022.8565.529
نویسندگان
M. R. Behbahani Nejad* 1؛ H. Rashidi2
1Faculty of Electrical Engineering, Computer, Information Technology and Bio-electric Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
2Faculty of Statistics, Mathematics and Computer Science, Allameh Tabataba’i University, Tehran, Iran.
تاریخ دریافت: 23 دی 1400،  تاریخ بازنگری: 12 خرداد 1401،  تاریخ پذیرش: 16 خرداد 1401 
چکیده
Background and Objectives: Big data is a combination of structured, semi-structured and unstructured data collected by organizations that must be stored and used for decision-making. Businesses that deal with the business intelligence system, as well as their data sources, have a major challenge in exploiting Big Data. The current architecture of business intelligence systems is not capable of incorporating and exploiting Big Data. In this paper, an architecture is developed to respond to this challenge.
Methods: This paper focuses on the promotion of business intelligence to create an ability to exploit Big Data in business intelligence. In this regard, a new architecture is proposed to integrate both Business Intelligence and Big Data architectures. To evaluate the proposed architecture, we investigated business intelligence architecture and Big Data architecture. Then, we developed a Unified Modeling Language diagram for the proposed architecture. In addition, using the Colored Petri-Net, the proposed architecture is evaluated in a case study.
Results: The results show that our architectural system has a higher efficiency in performing all steps, average time, and maximum time compared to business intelligence architecture.
Conclusion: The proposed architecture can help companies and organizations gain more value from their data sources and better support managers and organizations in their decision-making.
کلیدواژه‌ها
Architecture؛ Big Data؛ Business Intelligence؛ Hadoop؛ CPN
مراجع
[1] K. Batko, A. Ślęzak, “The use of big data analytics in healthcare,” J. Big Data, 9(3): 1-24, 2022.

[2] A. Heydarian, H. Rashidi, “Storage, and access system of self-adapting Health big data based on smart IoT (in Persian),” presented at the Fourth International Conference on Electrical, Computer and Mechanical Engineering, 2021.

[3] C. Dobre, F. Xhafa, “Intelligent services for big data science,” Future. Gener. Comput. Syst. 37: 267–281, 2014.

[4] G. Muhammad, J. Ibrahim, Z. Bhatti, A. Waqas, “Business intelligence as a knowledge management tool in providing financial consultancy services,” Am. J. Inf. Syst., 2(2): 26-32, 2014.

[5] "IEEE recommended practice for architectural description for software-intensive systems," IEEE Std 1471-2000: 1-30, 9 Oct. 2000.

[6] W. Pedryz, Architecture in Big Data, Information Granularity, Big Data, and Computational Intelligence, Studies in Big Data, 8: 275-295, 2015.

[7] L. Bass, P. Clements, R. Kazman, Software Architecture in Practice, 4th Edition, SEI Series in Software Architecture, Addison-Wesley Professional, 2021.

[8] L. Clements, B. Paul, Rick Kazman, Software Architecture in Practice, 2nd Edition, SEI Series in Software Architecture, Addison-Wesley Professional, 2003.

[9] R. N. Taylor, N. Medvidović, E. M. Dashofy, Software architecture: Foundations, Theory and Practice. Wiley, 2009.

[10] M. M. Patil.  Challenges and Issues in Handling Big Data, Int. J. Innovations Adv. Comput. Sci. )IJIACS(, 4)Special Issue:( 620 – 625, 2015.

[11] D. S. Linthicum, Service-Oriented Architecture (SOA)", Retrieved 09-21, 2016.

[12] P. Clements, K. Klein, Evaluating Software Architecture Methods and Case Studies, Addison Wesely, 2002.

[13] B. Kumar, J. Jaspernete, “UML profiles for modeling real-time communication protocols,” J. Object Tech., 9(2): 178-198, 2012.

[14] S. Balsamo, M. Marzolla, “A simulation-based approach to software performance modeling, ACM SIGSOFT software engineering notes,” in Proc. the 9th European Software Engineering Conference Held Jointly with 11th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 28(5): 363-366, 2003.

[15] J. Dong, “UML extensions for design pattern compositions,” J. O. Tech. 1(5): 151-163, 2002.

[16] F. Liangbing, M. Obayashi, T. Kuremoto, K. Kobayashi Construction and application of learning Petri net, Manufacturing and Computer Science, 143-176, 2012.

[17] M. Muntean, Collaborative Business Environment Based on Federated Portals, Annals of T. Popoviciu Seminar, 4: 218-224, 2006.

[18] R. Sharda, D. Dursun, T. Efraim, Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th edition, Pearson, Prentice-Hall, 2020.

[19] R. Erl, W. Khattak, P. Buhler, Big Data Fundamentals: Concepts, Drivers & Techniques, Pearson Service Technology Series from Thomas Erl, 1st Edition, 2017.

[20] D. Laney, “Application Delivery Strategies”, Gartner (META Group), White Paper, 2001.

[21] A. N. Nandakumar, N. Yambem,  “A survey on data mining algorithms on apache hadoop platform,” Int. J. Emerging Technol. Adv. Eng., 4(1): 263-265, 2014.

[22] M. R. BehbahaniNejad, H. Rashidi, M. J.  Tarokh, “Survey big data technologies architecture and the need to exploit it in DSS systems," presented at the 8th Iranian & 2th International Knowledge Management Conference, Tehran, 23-24 February 2016.

[23] S. R. Pakize, “A comprehensive view of Hadoop MapReduce Scheduling algorithms,” Int. J. Comput. Networks Commun. Secur., 2(9): 308–317, 2014.

[24] K. Kashyap, C. Deka, S. Rakshit, “A review on big data, Hadoop and Its impact on business,” Int. J. Innovative Res. Dev., 3(12): 78-82, 2014.

[25] A. Labrinidis, HV. Jagadish, Challenges, and opportunities with big data. Proc VLDB Endowment, 5(12): 2032–2033, 2012.

[26] M. Chen, S. Mao, Y. Liu, “Big data: A survey,” Mob. Netw. Appl. 19: 171–209, 2014.

[27] A. F. Mohammad, H. Mcheick, E. S. Grant, “Big data architecture evolution,” The fourth ACM International Symposium, 2014.

[28] Wikipedia.  “Apache Hadoop” .Retrieve from https://en.wikipedia.org/wiki/Apache_Hadoop , 2015.

[29] Lockwood, Conceptual Overview of Map-Reduce and Hadoop, 2015.

[30] M. R. Behbahani Nejad, H. Rashidi, “A data architecture architecture with business intelligence approach,” presented at the first Seminar on Data Science and applications: 14-15, Tehran, 2021.

[31] H. Rashidi, “Corporate planning using object-oriented rules and considering big data (in Persian),” Allameh Tabataba’i Press, 2018.

[32] S. Oluwaseun Fadiy, S. Saydamb, V. Vanyduhe, “Advancing big data for humanitarian needs,” Procedia Eng., 78: 88-95, 2014.

[33] F. Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D. A. Wallach, M. Burrows, “Bigtable: A distributed storage system for structured data,” J. ACM Trans. Comput. Syst. (TOCS), 26(2): 1-14, 2008.

[34] T. Poleto, V. DioghoHeuer de Carvalho, A. P. Cabral Seixas Costa, “the roles of big data in the decision-support process: An empirical investigation,” Decision Support Systems V – Big Data Analytics for Decision Making. ICDSST 2015. Lecture Notes in Business Information Processing, 216: 10–21, 2015.

[35] B. Sanjib, S. Jaydip, “A proposed framework of next generation supply chain management using big data analytics,” presented at the National Conference on Emerging Trends in Business and Management: Issues and Challenges, , Kolkata, INDIA, March 17-18, 2016.

[36] R. Rossi, K. Hirama, “Characterizing big data management,” Issues Informing Scie. Inform. Technol. 12: 165-180, 2015.

[37] H. Borut, J. Jaklič, “Assessing benefits of business intelligence systems–a case study,” Manage. J. Contemp. Manage. Issues, 15(1): 87-119, 2010.

[38] S. Eybers S, J. H Strydom, Towards a classification framework of business intelligence value research. Italian Chapter of AIS (itAIS 2013), 2013.

[39] A. Carver, M. Ritacco, The Business Value of Business Intelligence. A Framework for Measuring the Benefits of Business Intelligence. Business Objects, 2006.

[40] M. Bahrami, M. Singhal, “The role of cloud computing rchitectour in big data, Chapter: Information Granularity, Big Data, and Computational Intelligence, Volume 8 of the series Studies in Big Data: 275-295, 2015.

[41] P. Russom, Integrating Hadoop into business intelligence and data warehouse, TDWI research. S. Madden, MIT, 2013.

[42] A. Abroshan, A. Harounabadi, J. Mirabedini, “Evaluation of software architecture using fuzzy colored Petri nets,” Manage. Scie. Lett., 3: 665-682, 2013.

[43] K. Dwivedi, S. K. Dubey, “Analytical review on Hadoop distributed file system”, presented at the 5th International Conference on Confluence the Next Generation Information Technology Summit: 25-26, Noida, India, 2014.

[44] J. Wang, X. He, Y. Deng, “Introducing software architecture specification and analyzing in SAM through an Example,” Inform. Software Technol. J., 41(7): 451-467, 1999.

 

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