Design and Construction of a Big Data Analytics Framework for Health Applications

Abstract

We propose to establish a framework for supporting Big Data Analytics (BDA) on real healthcare big data. To test the analytic framework, we used UVic WestGrid (4412 cores computer cluster) to analyze the emulation of 10 billion healthcare records that represented the main hospital system and its reporting via its data warehouse stored at Vancouver Island Health Authority (VIHA). The study showed that the build of the BDA platform requires changes to the configurations to the MapReduce component of Hadoop (HDFS) and to the indexing of HBASE. The ingestion and replication of the data over a large volume iteratively offers a method for data migration of large volumes of real healthcare data via HDFS and to query in that some distributed filing system. Furthermore, the query performance was very satisfied via Apache Phoenix layer that is run in parallel across all nodes on HBASE. The study has demonstrated that the proposed BDA process and configuration met patient data security and performance requirements of healthcare BDA.

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