Operationalizing Machine Learning with Streaming Data Pipelines

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Presented by

Brad Murdoch, EVP of Strategy & Product, Lightbend

About this talk

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 can 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 session, we will discuss real-world examples of how streaming data can enable smarter business, the challenges of building streaming data pipelines and a proven approach to operationalizing data science into game-changing run-the-business systems.
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