Deploying real-time analytics projects at scale requires many steps, including data processing, model development, creation of a real-time process flow and deployment. This can be a tall order. Through the power of the end-to-end capabilities in SAS®, we've made this process simple and straightforward. We'll demonstrate using a project delivered in collaboration with ClearBlade, a SAS® partner. By entering just a few simple inputs, machine learning models are trained and deployed in real time to monitor energy output across all assets in the SAS solar farm. The ultra-agile approach retrieves data, builds comprehensive analytic datasets, trains models using a selected Model Studio pipeline, registers champion models to Model Manager, builds a real-time Event Stream Processing project and generates a deployable container that can be run in Docker or on a VM. Want to monitor the health of those models? Receive daily updates. Have a few minutes to attend? That's all you'll need to deploy world-class analytics in real time.
