Disrupting Healthcare Silos: Addressing Data Volume, Velocity and Variety With a Cloud-Native Healthcare Data Ingestion Service
Rohit Ranchal, Paul Bastide, Xu Wang, Aris Gkoulalas-Divanis, Maneesh Mehra, Senthil Bakthavachalam, Hui Lei, Ajay Mohindra
Abstract
Healthcare enterprises are starting to adopt cloud computing due to its numerous advantages over traditional infrastructures. This has become a necessity because of the increased volume, velocity and variety of healthcare data, and the need to facilitate data correlation and large-scale analysis. Cloud computing infrastructures have the power to offer continuous acquisition of data from multiple heterogeneous sources, efficient data integration, and big data analysis. At the same time, security, availability, and disaster recovery are critical factors aiding towards the adoption of cloud computing. However, the migration of healthcare workloads to cloud is not straightforward due to the vagueness in healthcare data standards, heterogeneity and sensitive nature of healthcare data, and many regulations that govern its usage. This paper highlights the need for providing healthcare data acquisition using cloud infrastructures and presents the challenges, requirements, use-cases, and best practices for building a state-of-the-art healthcare data ingestion service on cloud.