INTEGRATING SNOWFLAKE AND AI FOR CLOUD-BASED DATA WAREHOUSING IN OIL & GAS OPERATIONS
Keywords:
Cloud Data Warehousing, Artificial Intelligence, Oil And Gas Operations, Predictive Analytics,, IoT Device ManagementAbstract
A. K. Sahu and R. Kumar, "Digital Transformation in Oil and Gas Industry: Developing an OSDU Third-Party Application," 2021 International Conference on Engineering and Emerging Technologies (ICEET), IEEE, 2021. https://ieeexplore.ieee.org/abstract/document/9659636
[2] S. M. Rahman and M. A. Rahman, "The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry: Envisaging AI-inspired Intelligent Energy Systems and Environments," IEEE Press, 2024. https://ieeexplore.ieee.org/book/10347488
[3] S. K. Sharma and D. Kumar, "Scalable Architectures to Support Sustainable Advanced Information Technologies," 2022 IEEE International Conference on Cluster Computing (CLUSTER), IEEE, 2022. https://ieeexplore.ieee.org/document/9912677
[4] R. Buyya and M. Singh, "On Efficiency and Scalability of Software-Defined Infrastructure for Cloud Computing," 2016 IEEE International Conference on Autonomic Computing (ICAC), IEEE, 2016. https://ieeexplore.ieee.org/document/7573113
[5] A. Johnson and R. Kumar, "Autonomic Coordination of IoT Device Management Platforms," 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), IEEE, 2020. https://ieeexplore.ieee.org/document/9338591
[6] F. Ouyang, M. Wu, L. Zheng, L. Zhang, and P. Jiao, "Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course," International Journal of Educational Technology in Higher Education, 2023. https://link.springer.com/article/10.1007/s13132-024-02001-z
[7] Z. Zong and Y. Guan, "AI-Driven Intelligent Data Analytics and Predictive Analysis in Industry 4.0: Transforming Knowledge, Innovation, and Efficiency," Journal of the Knowledge Economy, 2024. https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-022-00372-4
[8] M. Thompson and R. Kumar, "Data Integration Revitalized: From Data Warehouse Through Data Lake to Data Mesh," 2024 IEEE International Conference on Data Engineering (ICDE), IEEE, 2024. https://link.springer.com/chapter/10.1007/978-3-031-39847-6_1
[9] L. Zhang and S. Chen, "Multi-source Data Sharing of Electrical Equipment Based on Handle System Identity Resolution Technology for Internet of Things in Electric Industry," 2021 International Conference on Intelligent Computing, Automation and Systems (ICICAS), IEEE, 2021. https://ieeexplore.ieee.org/abstract/document/9723789
[10] Z. Bučinca, M. B. Malaya, and K. Z. Gajos, "To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making," Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, ACM, 2021. https://scholar.harvard.edu/files/zbucinca/files/bucinca2021trust.pdf
[11] X. Vasques, "Machine Learning Theory and Applications: Hands-on Use Cases with Python on Classical and Quantum Machines," IEEE Press, 2023. https://ieeexplore.ieee.org/book/10444091
[12] M. Rahman and K. Kumar, "Governance Life Cycle Framework for Managing Security in Public Cloud: From User Perspective," IEEE Transactions on Cloud Computing, vol. 12, no. 2, pp. 45-60, 2023. https://ieeexplore.ieee.org/document/6008732
[13] J. Chen and R. Smith, "A Conceptual Framework of IT Security Governance and Internal Controls," IEEE Security & Privacy, vol. 18, no. 4, pp. 78-92, 2022. https://ieeexplore.ieee.org/abstract/document/8626831
[14] A. Jaara, A. Hamdan, and S. Mushtaha, "The Impact of Artificial Intelligence (AI) in the Oil and Gas Industry," Studies in Computational Intelligence, vol. 1037, Springer, 2022. https://link.springer.com/chapter/10.1007/978-3-030-99000-8_29
References
A. K. Sahu and R. Kumar, "Digital Transformation in Oil and Gas Industry: Developing an OSDU Third-Party Application," 2021 International Conference on Engineering and Emerging Technologies (ICEET), IEEE, 2021. https://ieeexplore.ieee.org/abstract/document/9659636
S. M. Rahman and M. A. Rahman, "The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry: Envisaging AI-inspired Intelligent Energy Systems and Environments," IEEE Press, 2024. https://ieeexplore.ieee.org/book/10347488
S. K. Sharma and D. Kumar, "Scalable Architectures to Support Sustainable Advanced Information Technologies," 2022 IEEE International Conference on Cluster Computing (CLUSTER), IEEE, 2022. https://ieeexplore.ieee.org/document/9912677
R. Buyya and M. Singh, "On Efficiency and Scalability of Software-Defined Infrastructure for Cloud Computing," 2016 IEEE International Conference on Autonomic Computing (ICAC), IEEE, 2016. https://ieeexplore.ieee.org/document/7573113
A. Johnson and R. Kumar, "Autonomic Coordination of IoT Device Management Platforms," 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), IEEE, 2020. https://ieeexplore.ieee.org/document/9338591
F. Ouyang, M. Wu, L. Zheng, L. Zhang, and P. Jiao, "Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course," International Journal of Educational Technology in Higher Education, 2023. https://link.springer.com/article/10.1007/s13132-024-02001-z
Z. Zong and Y. Guan, "AI-Driven Intelligent Data Analytics and Predictive Analysis in Industry 4.0: Transforming Knowledge, Innovation, and Efficiency," Journal of the Knowledge Economy, 2024. https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-022-00372-4
M. Thompson and R. Kumar, "Data Integration Revitalized: From Data Warehouse Through Data Lake to Data Mesh," 2024 IEEE International Conference on Data Engineering (ICDE), IEEE, 2024. https://link.springer.com/chapter/10.1007/978-3-031-39847-6_1
L. Zhang and S. Chen, "Multi-source Data Sharing of Electrical Equipment Based on Handle System Identity Resolution Technology for Internet of Things in Electric Industry," 2021 International Conference on Intelligent Computing, Automation and Systems (ICICAS), IEEE, 2021. https://ieeexplore.ieee.org/abstract/document/9723789
Z. Bučinca, M. B. Malaya, and K. Z. Gajos, "To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making," Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, ACM, 2021. https://scholar.harvard.edu/files/zbucinca/files/bucinca2021trust.pdf
X. Vasques, "Machine Learning Theory and Applications: Hands-on Use Cases with Python on Classical and Quantum Machines," IEEE Press, 2023. https://ieeexplore.ieee.org/book/10444091
M. Rahman and K. Kumar, "Governance Life Cycle Framework for Managing Security in Public Cloud: From User Perspective," IEEE Transactions on Cloud Computing, vol. 12, no. 2, pp. 45-60, 2023. https://ieeexplore.ieee.org/document/6008732
J. Chen and R. Smith, "A Conceptual Framework of IT Security Governance and Internal Controls," IEEE Security & Privacy, vol. 18, no. 4, pp. 78-92, 2022. https://ieeexplore.ieee.org/abstract/document/8626831
A. Jaara, A. Hamdan, and S. Mushtaha, "The Impact of Artificial Intelligence (AI) in the Oil and Gas Industry," Studies in Computational Intelligence, vol. 1037, Springer, 2022. https://link.springer.com/chapter/10.1007/978-3-030-99000-8_29