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Integrating Scalable Analytical Tools and Data Warehouses on Private Cloud
Kazumasa Kishimoto1,2, Osamu Sugiyama3, Tomohide Iwao1,2
1Kyoto University, Kyoto, Japan.
Abstract:
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.
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