A Hybrid Transaction Processing and Data Analysis Framework: A Use Case Study for Multi-Source Healthcare Data Management

Rapidly growing data volume demand systems that have the ability to handle massive heterogeneous unstructured data sets in digital home environment. However, currently, most existing mature transaction processing systems are built upon relational databases with structured data. In this paper, we design a hybrid development framework, to offer greater scalability and flexibility of data analysis and report, while keeping maximum compatibilities and links to the legacy platforms on which transaction business logics run. Data, service and user interfaces are implemented as a toolset stack, for developing applications with functionalities of information retrieval, data processing, analysing and visualizing. We discuss a use case of healthcare data integration as an example, where information is collected and aggregated from diverse sources such as electronic health records (EHRs), personal health records (PHRs) and wearable devices. We present the workflow of data processing and visualization, to validate the effectiveness of the proposed framework.