WEBINAR | ON-DEMAND
Machine Learning in Action: Applying ML to Real-Time Streams of Data
Brad Murdoch, EVP, Strategy and Product at Lightbend, Inc.
Adam Leszinski, Global Solutions Architect at Lightbend, Inc.
Organizations invest in big data to get more insight into their business. They further invest in data science teams to build and train machine learning (ML) models for making better business decisions. Both are excellent steps, but the greatest value can be realized when true operationalization of data for real-time business decisions and customer optimization can take place. And that requires streaming data pipelines.
Streaming data pipelines enable enterprises to take advantage of real-time data with examples such as recommendation engines, real-time personalization, real-time risk analysis, real-time supply chain optimization, IoT operational controls, and financial services processes.
In this webinar, Brad Murdoch and Adam Leszinksi explore real-world examples of how streaming data can enable smarter business decisions, the challenges of building streaming data pipelines, and demo a proven solution to operationalizing machine learning into game-changing, run-the-business systems.