Integrating MATLAB Analytics into Enterprise Applications

As the size and variety of your engineering data has grown, so has the capability to access, process, and analyze those (big) engineering data sets in MATLAB^®. With the rise of streaming data technologies, the volume and velocity of this data has increased significantly, and this has motivated new approaches to handle data-in-motion. Jim Stewart discusses the use of MATLAB as a data analytics platform with best-in-class frameworks and infrastructure to express MATLAB based workflows that enable decision making in “real-time” through the application of machine learning models. He demonstrates how to use MATLAB Production Server™ to deploy these models on streams of data from Apache^® Kafka^®. The demonstration shows a full workflow from the development of a machine learning model in MATLAB to deploying it to work with a real-world sized problem running on the cloud.