Microsoft Azure - A case study

Contoso Health Network recently deployed IoT devices to its Intensive Care Unit, ICU. Here are the goals of the project -

1. Capture data on patient bio-metric monitoring in real time to help physicians treat their patients, store the bio-metric data so that Contoso's Research Center can further analyze it in the future.
2. Use Azure Machine Learning to understand which treatments improve the quality of care and reduce the likelihood that a patient will be re-admitted to the hospital.
3. Create a visualization of the data's history for Contoso's Chief Medical Officer.
4. After reviewing the business case, Contoso's Technical Architect proposes the following technologies.
5. Azure IoT Hub to capture real-time data from the ICU's IoT devices, Azure Stream Analytics to stream and enrich the IoT data to create windows and aggregations, and to integrate Azure Machine Learning.
6. Azure Data Lake Storage Generation 2 to store the bio-metric data at high-speed, Azure Data Factory to perform the extract load transform and final load.
7. Azure Synapse Analytics to provide data warehousing and big data engineering services to support the Chief Medical Officer's needs.
8. Power BI to create the patient dashboard. Part of the dashboard will show real-time telemetry about the patient's condition, the other part will show the patient's recent history, and Azure Machine Learning to process both raw and aggregated data. Researchers will use this to perform predictive analytics on patient re admittance.
9. Contoso's Data Engineer creates a work plan to implement the ELT Operations.
10. The plan includes a provisioning workflow and holistic workflow.
11. This is the provisioning workflow. Provision Azure Data Lake Storage Gen 2,Provision Azure Synapse Analytics, Provision Azure IoT Hub, Provision Azure Stream Analytics, Provision Azure Machine Learning, Provision Azure Data Factory, and Provision Power BI.
12. The plan for the holistic workflow is to set up Azure IoT Hub to capture data from the ICU IoT devices. Connect Azure IoT Hub to Azure Stream Analytics. Set up window creation functions for the ICU data. The functions will aggregate the data for each window. At the same time, set up the IoT Hub to move the streaming data to Azure Data Lake Storage by using Azure Functions. Set up Azure Functions to store the Azure Stream Analytics aggregates in Azure Data Lake Storage Gen 2.Use Azure Data Factory to load data from the Data Lake into Azure Synapse Analytics to support the Chief Medical Officer's needs.
13. After the data is loaded, transformations can occur within Azure Synapse Analytics. 
14. In parallel, connect the Azure Machine Learning Service to Azure Data Lake Storage to perform predictive analytics. Connect Power BI to stream analytics to pull the real-time aggregates for the patient data. Connect Azure Synapse Analytics to pull the historical data to create a combined dashboard. Contoso Health Network's project was to deploy IoT devices to its ICU.

Refer and credit - Coursera and Microsoft