Below is a diagram that shows how we implemented open-source technologies to aggregate large volumes of real-time data, process that data with complex rules, and perform analytics on real-time streaming data:
With the advent of IoT and device integration, organizations are realizing the need to collect and
interpret data in real time. This paradigm shift in data handling helps them anticipate, meet, and
predict customer needs. This dramatically enhances their customer satisfaction index.
Below is a diagram that shows how we implemented open-source technologies to aggregate large volumes of real-time data, process that data with complex rules, and perform analytics on real-time streaming data:
How are data training and prediction wired together?
Our Technology Stack
Since this is an app demo, we are not interacting directly with IoT devices to fetch information in real time. Instead, we are simulating the real-time information through a producer module from a database. The data for this producer module is read from the database, which we call a simulated, real-time dataset.
The iHealth app demo is HIPAA and HITECH compliant. To learn more about how we build security-compliant data analytics solutions for the healthcare industry, please see our whitepaper, “HIPAA Compliance on the Cloud,” here.