Implementing Data Lakes in Healthcare Enterprises: Architecture, Benefits, and Challenges

Abstract

This work will review the process of using data lakes in healthcare companies, focusing on their frameworks, the benefits they provide and the difficulties involved. Bringing structured and unstructured data into a data lake means one can save more data, use analytics better and rely on AI to make decisions. The approach assesses healthcare architectures such as TOGAF and proves faster data absorption, more efficient queries and improved information coverage. Several case studies and prototype experiments explain how clinical research, treating patients and running services have improved. The study confirms that data lakes are helping to modernize healthcare analytics and highlights the need for good governance, interoperability and adherence to regulations for them to work well in healthcare.