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The Impact of Artificial Intelligence on Big Data Analysis and Digital Transformation
Subject area: Science,Engineering and Technology · Area of research: Technology
Abstract
Big Data analysis, driven by Artificial Intelligence (AI), has become essential for digital transformation across various sectors. The increasing volume of generated data demands powerful tools like AI to process, interpret, and extract valuable insights. Companies of all sizes have adopted AI to optimize operations, personalize products, and improve customer experience. Machine learning algorithms and neural networks are used to identify patterns and trends in large datasets, a task impossible to achieve manually. In the e-commerce sector, AI predicts purchasing behaviors and personalizes recommendations. In biotechnology and climate science, it facilitates essential discoveries, such as new treatments and solutions. Additionally, AI has transformed healthcare through personalized medicine and helped predict demand and perform predictive maintenance in industries like manufacturing and energy. Real-time data processing, offered by AI, is a strategic advantage in areas like the financial market, where rapid decision-making is crucial. Despite advancements, ethics, privacy, and algorithm transparency are challenges that must be addressed. The collection and use of personal data require rigorous security and transparent practices. The integration of AI and Big Data is transforming business decision-making, making it more data-driven and insight-based. However, this revolution also requires ethical reflection, particularly regarding the use of sensitive data and corporate responsibility. The future of AI and Big Data demands a balanced approach, with technological innovation and ethical commitment, to maximize its social and economic benefits.
Keywords
Big Data, Artificial Intelligence, Digital Transformation, Algorithms, Ethics.
References
[1] Eboigbe, E., Farayola, O., Olatoye, F., Nnabugwu, O., & Daraojimba, C. (2023). Business Intelligence transformation through AI and data analytics. Engineering Science & Technology Journal. https://doi.org/10.51594/estj.v4i5.616.
[2] Johri, S., Rawal, K., Aishwarya, B., Singh, N., Shaaker, A., & , R. (2023). Big Data and Artificial Intelligence: Revolutionizing Business Decision-Making. 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 10, 1689-1693. https://doi.org/10.1109/UPCON59197.2023.10434500.
[3] Lakhan, N. (2022). Applications of Data Science and AI in Business. International Journal for Research in Applied Science and Engineering Technology. https://doi.org/10.22214/ijraset.2022.43343.
[4] Nesterov, V. (2024). Optimization of Big Data Processing and Analysis Processes in the Field of Data Analytics Through the Integration of Data Engineering and Artificial Intelligence. Computer-integrated technologies: education, science, production. https://doi.org/10.36910/6775-2524-0560-2024-54-19.
[5] Radha, C., Midunkumar, R., Muralibabu, S., & Partheeban, V. (2024). Role of Artificial Intelligence in Big Data Analytics. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-17089.
[6] Zaripova, R., Kosulin, V., Shkinderov, M., & Rakhmatullin, I. (2023). Unlocking the potential of artificial intelligence for big data analytics. E3S Web of Conferences. https://doi.org/10.1051/e3sconf/202346004011.
[7] Delci, C. A. M. (2025). THE EFFECTIVENESS OF LAST PLANNER SYSTEM (LPS) IN INFRASTRUCTURE PROJECT MANAGEMENT. Revista Sistemática, 15(2), 133–139. https://doi.org/10.56238/rcsv15n2-009
[8] SANTOS,Hugo;PESSOA,EliomarGotardi.Impactsofdigitalizationontheefficiencyandqualityofpublicservices:Acomprehensiveanalysis.LUMENETVIRTUS,[S.l.],v.15,n.40,p.44094414,2024.DOI:10.56238/levv15n40024.Disponívelem:https://periodicos.newsciencepubl.com/LEV/article/view/452.Acessoem:25jan.2025.
[9] Freitas,G.B.,Rabelo,E.M.,&Pessoa,E.G.(2023).Projetomodularcomreaproveitamentodecontainermaritimo.BrazilianJournalofDevelopment,9(10),28303–28339.https://doi.org/10.34117/bjdv9n10057
[10] Freitas,G.B.,Rabelo,E.M.,&Pessoa,E.G.(2023).Projetomodularcomreaproveitamentodecontainermaritimo.BrazilianJournalofDevelopment,9(10),28303–28339.https://doi.org/10.34117/bjdv9n10057
[11] Pessoa,E.G.,Feitosa,L.M.,ePadua,V.P.,&Pereira,A.G.(2023).EstudodosrecalquesprimáriosemumaterroexecutadosobreaargilamoledoSarapuí.BrazilianJournalofDevelopment,9(10),28352–28375.https://doi.org/10.34117/bjdv9n10059
[12] PESSOA,E.G.;FEITOSA,L.M.;PEREIRA,A.G.;EPADUA,V.P.Efeitosdeespéciesdealnaeficiênciadecoagulação,Alresidualepropriedadedosflocosnotratamentodeáguassuperficiais.BrazilianJournalofHealthReview,[S.l.],v.6,n.5,p.2481424826,2023.DOI:10.34119/bjhrv6n5523.Disponívelem:https://ojs.brazilianjournals.com.br/ojs/index.php/BJHR/article/view/63890.Acessoem:25jan.2025.
[13] SANTOS,Hugo;PESSOA,EliomarGotardi.Impactsofdigitalizationontheefficiencyandqualityofpublicservices:Acomprehensiveanalysis.LUMENETVIRTUS,[S.l.],v.15,n.40,p.44094414,2024.DOI:10.56238/levv15n40024.Disponívelem:https://periodicos.newsciencepubl.com/LEV/article/view/452.Acessoem:25jan.2025.
[14] Filho, W. L. R. (2025). The Role of Zero Trust Architecture in Modern Cybersecurity: Integration with IAM and Emerging Technologies. Brazilian Journal of Development, 11(1), e76836. https://doi.org/10.34117/bjdv11n1-060
[15] Oliveira, C. E. C. de. (2025). Gentrification, urban revitalization, and social equity: challenges and solutions. Brazilian Journal of Development, 11(2), e77293. https://doi.org/10.34117/bjdv11n2-010
[16] Filho, W. L. R. (2025). THE ROLE OF AI IN ENHANCING IDENTITY AND ACCESS MANAGEMENT SYSTEMS. International Seven Journal of Multidisciplinary, 1(2). https://doi.org/10.56238/isevmjv1n2-011
How to cite this paper
@article{1707393,
author = {Rafael Carvalho Turatti},
title = {The Impact of Artificial Intelligence on Big Data Analysis and Digital Transformation},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {9},
pages = {253-257},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707393.pdf},
abstract = {Big Data analysis, driven by Artificial Intelligence (AI), has become essential for digital transformation across various sectors. The increasing volume of generated data demands powerful tools like AI to process, interpret, and extract valuable insights. Companies of all sizes have adopted AI to optimize operations, personalize products, and improve customer experience. Machine learning algorithms and neural networks are used to identify patterns and trends in large datasets, a task impossible to achieve manually. In the e-commerce sector, AI predicts purchasing behaviors and personalizes recommendations. In biotechnology and climate science, it facilitates essential discoveries, such as new treatments and solutions. Additionally, AI has transformed healthcare through personalized medicine and helped predict demand and perform predictive maintenance in industries like manufacturing and energy. Real-time data processing, offered by AI, is a strategic advantage in areas like the financial market, where rapid decision-making is crucial. Despite advancements, ethics, privacy, and algorithm transparency are challenges that must be addressed. The collection and use of personal data require rigorous security and transparent practices. The integration of AI and Big Data is transforming business decision-making, making it more data-driven and insight-based. However, this revolution also requires ethical reflection, particularly regarding the use of sensitive data and corporate responsibility. The future of AI and Big Data demands a balanced approach, with technological innovation and ethical commitment, to maximize its social and economic benefits.},
keywords = {Big Data, Artificial Intelligence, Digital Transformation, Algorithms, Ethics.},
month = {March},
}