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English Information

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Authors
# Name
1 Arthur Bezerra(arthur.bezerra@lge.com)
2 Iranildo Batalha(iranildo.batalha@lge.com)
3 Luís Filho(luis.filho@lge.com)
4 Clarice Almeida(clarice.almeida@lge.com)
5 Matheus Dantas(matheus.dantas@lge.com)
6 Nelson Gouvêa(nelson.gouvea@lge.com)

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Reference
# Reference
1 Giebler, C., Gröger, C., Hoos, E., Eichler, R., Schwarz, H., and Mitschang, B. (2021). The data lake architecture framework: A foundation for building a comprehensive data lake architecture.
2 Imperva (2024). Imperva 2024 bad bot report. Technical report, Imperva Inc. Accessed: 2025-05-19.
3 Khine, Pwint Phyu and Wang, Zhao Shun (2018). Data lake: a new ideology in big data era. ITM Web Conf., 17:03025.
4 Kothandapani, H. P. (2021). Integrating robotic process automation and machine learning in data lakes for automated model deployment, retraining, and data-driven decision making.
5 Minh, T. P., Quang, H. H., and Manh, T. N. (2024). A zone-based data lake architecture for smart crop farming in vietnam: A strategic perspective. In Proceedings of the 2nd International Conference - Resilience by Technology and Design (RTD 2024), pages 29-44. Atlantis Press.
6 Nargesian, F., Zhu, E., Miller, R. J., Pu, K. Q., and Arocena, P. C. (2019). Data lake management: challenges and opportunities. Proc. VLDB Endow., 12(12):1986-1989.
7 Pereira, A. and Simonetto, E. (2018). Indústria 4.0: Conceitos e perspectivas para o brasil. Revista da Universidade Vale do Rio Verde, 16(1). Doutorando e professor do Programa de Pós-Graduação em Administração, UFSM.
8 Ribeiro, J., Lima, R., Eckhardt, T., and Paiva, S. (2021). Robotic process automation and artificial intelligence in industry 4.0 – a literature review. Procedia Computer Science, 181:51–58. CENTERIS 2020 - International Conference on ENTERprise Information Systems / ProjMAN 2020 - International Conference on Project MANagement / HCist 2020 - International Conference on Health and Social Care Information Systems and Technologies 2020, CENTERIS/ProjMAN/HCist 2020.
9 Rodrigues, J. and Mello, R. (2022). Um estudo sobre arquiteturas e metadados em data lakes. In Anais da XVII Escola Regional de Banco de Dados, pages 131-134, Porto Alegre, RS, Brasil. SBC.
10 Shukla, S. (2022). Developing pragmatic data pipelines using apache airflow on google cloud platform. INTERNATIONAL JOURNAL OF COMPUTER SCIENCES AND ENGINEERING, 10:1-8.
11 Tito, L., Motinha, C., Santiago, F., Ocaña, K., Bedo, M., and de Oliveira, D. (2020). Xi-dl: um sistema de gerência de data lake para monitoramento de dados da saúde. In Anais do XXXV Simpósio Brasileiro de Bancos de Dados, pages 151-156, Porto Alegre, RS, Brasil. SBC.
12 Vasconcelos, F. F. and Coutinho, F. J. (2024). Data lakehouses para a análise de dados geoespaciais em larga escala. In Anais do XXXIX Simpósio Brasileiro de Bancos de Dados, pages 722-728, Porto Alegre, RS, Brasil. SBC.
13 Yang, C.-T., Chen, T.-Y., Kristiani, E., and Wu, S. F. (2021). The implementation of data storage and analytics platform for big data lake of electricity usage with spark. The Journal of Supercomputing, 77(6):5934-5959.