AI-Driven Data Warehouse Modernization in the Healthcare Sector: A Blueprint for Efficiency Modernizing Legacy Data Warehouses with AI-Enhanced Workflows

Authors- Srinivasa Chakravarthy Seethala

Abstract-The healthcare industry is at a pivotal moment in terms of data management. Legacy data warehouses, which once served the sector’s needs, are now proving inefficient in an era of rapid technological advancements. This article proposes a framework for modernizing these legacy systems with Artificial Intelligence (AI) technologies, particularly AI-enhanced Extract, Transform, Load (ETL) workflows. These technologies have the potential to significantly improve data quality, operational efficiency, and scalability, especially in key areas such as Electronic Health Records (EHRs), Medical Imaging, Hospital Management, and Medical Research. Additionally, AI enables predictive analytics, offering healthcare organizations the ability to anticipate patient needs and optimize resource allocation. This paper explores the challenges healthcare organizations face, the benefits of AI-driven solutions, and best practices for implementation.

DOI: /10.61463/ijset.vol.4.issue5.108