Integrating Scalable Analytical Tools and Data Warehouses on Private Cloud.

This study addresses the need for efficient and scalable data warehouse solutions by integrating on-premises environments with private cloud-based infrastructures. Kubernetes was employed to dynamically generate secure virtual machines, offering users independent environments for data analysis. Performance testing demonstrated query speeds, with 240,000 records extracted from a 301GB dataset in 12.4 seconds. Security measures, using a VPN connection between hospital networks and Google Cloud, allowed the safe use of Google's APIs. This scalable infrastructure can accommodate diverse analytical needs.