Transforming Healthcare Data Warehouses with AI : Future-Proofing Through Advanced ETL and Cloud Integration

Authors

  • Srinivasa Chakravarthy Seethala   Lead Developer, Buffalo, New York, USA

DOI:

https://doi.org/10.32628/CSEIT23902180

Keywords:

Healthcare Data Warehousing, Artificial Intelligence, Cloud Computing, ETL Processes, Real-Time Processing, Predictive Analytics, Data Integration, Healthcare Data Governance, NLP in Healthcare, Population Health Management.

Abstract

The healthcare industry is undergoing a significant transformation in data management, spurred by the integration of artificial intelligence (AI) and cloud technologies in data warehousing. This paper investigates the transformative potential of AI-driven Extract, Transform, Load (ETL) processes and cloud integration within healthcare data warehouses. We explore how these technologies address key challenges such as data integration, real-time processing, and scalability, which are critical in healthcare environments. By examining various applications and proposing an implementation framework, this study provides a roadmap for optimizing healthcare data warehouses to support enhanced patient care, operational efficiency, and advanced analytics capabilities.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-04-16

Issue

Volume 9, Issue 2, March-April-2023

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Srinivasa Chakravarthy Seethala , " Transforming Healthcare Data Warehouses with AI : Future-Proofing Through Advanced ETL and Cloud Integration" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.749-752, March-April-2023. Available at doi : https://doi.org/10.32628/CSEIT23902180