Cloud-Native Data Warehousing: Implementing AI and Machine Learning for Scalable Business Analytics

Authors

  • Jeshwanth Reddy Machireddy Sr. Software Developer, Kforce INC, Wisconsin, USA Author
  • Sareen Kumar Rachakatla Lead Developer, Intercontinental Exchange Holdings, Inc., Atlanta, USA Author
  • Prabu Ravichandran Sr. Data Architect, Amazon Web services, Inc., Raleigh, USA Author

Keywords:

cloud-native data warehousing, artificial intelligence

Abstract

Business analytics paradigm shift cloud-native data warehousing is driven by scalable and efficient data management. AI/ML-enabled cloud-native data warehousing increases business analytics. These companies are replacing on-premises data warehousing with cloud-native architectures that take advantage of cloud computing's flexibility, scalability, and affordability.
Cloud-native data warehousing with AI and ML may improve corporate analytics, predictive modeling, and automated decision-making. AI/ML architectures for cloud-native data warehousing are examined here. Data warehouses optimize raw data for analytical queries, whereas data lakes hold huge amounts. Hybrid deployments using cloud-native technologies and AI-driven analytics are also covered.

References

J. D. M. Harvey, "Cloud Data Warehousing: Concepts and Architectures," IEEE Cloud Computing, vol. 7, no. 2, pp. 50-60, March-April 2020.

K. Chen and S. Wang, "Integrating AI and ML in Cloud-Based Data Warehousing Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 32, no. 5, pp. 1012-1023, May 2021.

T. S. Nguyen and M. K. Patel, "Performance Optimization for Cloud-Native Data Warehousing," IEEE Access, vol. 8, pp. 15323-15335, 2020.

P. Kumar, M. R. Tannenbaum, and M. Y. Chowdhury, "A Comparative Analysis of Cloud-Native Data Warehousing Architectures," IEEE Transactions on Cloud Computing, vol. 9, no. 3, pp. 778-789, July-September 2021.

R. Singh, A. S. Gupta, and H. Q. Li, "Data Integration and Quality in Cloud-Native Environments," IEEE Transactions on Big Data, vol. 7, no. 2, pp. 254-265, June 2021.

C. R. Robinson and L. Zhang, "AI and ML in Cloud Data Warehousing: Tools and Techniques," IEEE Transactions on Automation Science and Engineering, vol. 18, no. 4, pp. 1125-1136, October 2021.

M. J. Smith and E. G. Williams, "Scalability Challenges in Cloud Data Warehousing," IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 6, pp. 1440-1452, June 2021.

A. N. Moore and S. A. Brown, "Optimizing Cloud-Native Data Warehousing with Machine Learning," IEEE Transactions on Network and Service Management, vol. 17, no. 1, pp. 150-162, March 2021.

L. A. Martinez and Y. H. Lee, "Advanced Data Partitioning Techniques in Cloud Data Warehousing," IEEE Transactions on Cloud Computing, vol. 8, no. 4, pp. 878-889, October-December 2020.

B. K. Davis and M. J. George, "Benchmarking Cloud-Based Data Warehousing Systems," IEEE Transactions on Computers, vol. 70, no. 6, pp. 888-900, June 2021.

S. S. Patel and P. J. Singh, "Data Governance in Cloud-Native Data Warehousing: Best Practices and Solutions," IEEE Transactions on Information Forensics and Security, vol. 16, no. 2, pp. 500-512, February 2021.

H. B. Kim and T. A. Nguyen, "Security Challenges in Cloud Data Warehousing: A Survey," IEEE Transactions on Dependable and Secure Computing, vol. 18, no. 3, pp. 843-856, May-June 2021.

J. R. Lee and F. C. Yang, "Automated Data Cleansing in Cloud-Native Data Warehousing," IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 1, pp. 56-68, January 2022.

M. W. Li and K. T. Wang, "Efficient Query Optimization Techniques for Cloud Data Warehousing," IEEE Transactions on Database Systems, vol. 46, no. 4, pp. 1034-1046, December 2021.

R. G. Taylor and A. L. O’Connor, "Federated Learning for Cloud-Based Data Analytics," IEEE Transactions on Machine Learning and AI, vol. 7, no. 2, pp. 189-202, April 2022.

D. J. Moore and C. H. Zhang, "AI-Driven Data Management in Cloud Data Warehousing," IEEE Transactions on Emerging Topics in Computing, vol. 9, no. 1, pp. 114-126, January-March 2021.

E. M. Patel and V. A. Sharma, "Cloud-Native Data Warehousing for Real-Time Analytics: Techniques and Challenges," IEEE Transactions on Big Data, vol. 8, no. 3, pp. 332-345, September 2021.

F. C. Brown and J. M. King, "The Impact of Cloud Computing on Data Warehousing Strategies," IEEE Transactions on Cloud Computing, vol. 10, no. 2, pp. 650-663, April-June 2022.

L. T. White and S. P. Sharma, "Model Training and Validation in Cloud-Based Data Warehousing," IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 8, pp. 1876-1889, August 2021.

N. C. Kumar and M. S. Patel, "Emerging Trends in Cloud-Native Data Warehousing and AI Integration," IEEE Access, vol. 9, pp. 20812-20825, 2021.

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Published

30-06-2022

How to Cite

[1]
Jeshwanth Reddy Machireddy, Sareen Kumar Rachakatla, and Prabu Ravichandran, “Cloud-Native Data Warehousing: Implementing AI and Machine Learning for Scalable Business Analytics ”, Journal of AI in Healthcare and Medicine, vol. 2, no. 1, pp. 144–170, Jun. 2022, Accessed: Mar. 14, 2025. [Online]. Available: https://jaihmjournal.org/index.php/jaihm/article/view/4