Create a health data analytics app with legacy mainframe code and the cloud

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Summary

Summmit Health, a fictional healthcare and insurance company, has a Node.js-based analytics web application for a health records system. The web application is designed to showcase the best in class integration of modern cloud technology in collaboration with legacy mainframe code.

Description

Summit Health’s premise is that it has been around for a long time and has several hundreds of thousands in patient records on an SQL database connected to a z/OS mainframe. Summit Health’s records look very similar to the health records of most insurance companies that exist today.

Summit Health has recently started to understand how data science and analytics on some of the patient records might surface interesting insights. Summit Health has also heard a lot about cloud computing and would like to implement app modernization. There is a lot of legacy code in the mainframe and it works well for now, but Summit Health thinks it may be a timely opportunity to explore some data science and analytics in the cloud.

Flow

Using Kubernetes

Kubernetes flow

Using Cloud Foundry

Cloud Foundry flow

  1. The Data Service API acts as a data pipeline and is triggered to update the data lake with updated health records by calling API Connect APIs associated with the z/OS Mainframe.
  2. APIs from API Connect process relevant health records data from z/OS Mainframe data warehouse and send the data through the data pipeline.
  3. The Data Service data pipeline processes the z/OS Mainframe data and updates the MongoDB data lake.
  4. Users interact with the UI to view and analyze analytics.
  5. When the user interacts with the app, the UI is handled by Node.js where the API calls are initialized.
  6. The API calls are processed in the Node.js data service and are handled accordingly.
  7. The data is gathered from the MongoDB data lake from the API calls.
  8. The responses from the API calls are handled by the application’s UI.

Instructions

Find the detailed instructions in the README. These steps show you how to:

  1. Get a Mapbox Access Token to make the API calls.
  2. Run the application using data on the zOS Mainframe or by generating data.
  3. Deploy to the cloud using either Kubernetes or Cloud Foundry.