Operationalizing Data Science Models on the Pivotal Stack


At Pivotal Data Science, our primary charter is to help our customers derive value from their data assets, be it in the reduction of cost or by increasing revenue by offering better products and services. While we are not working on customer engagements, we engage in R&D using our wide array of products. For instance, we may contribute a new module to PDLTools or MADlib - our distributed in-database machine learning libraries, we might build end-to-end demos such as these or experiment with new technology and blog about them here. Last quarter, we set out to explore data science microservices for operationalizing our models for real-time scoring. Microservices have been the most talked about topic in many Cloud conferences of late. They've gained a large fan following by application developers, solution architects, data scientists and engineers alike.