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Keynote | Technical

Engineering analytics for predictive health applications

Thursday 16th | 16:35 - 17:05 | Theatre 19

Keywords defining the session:

- Agility

- Machine Learning

- Pipeline

As big data frameworks mature, solutions build around these technologies provide an increased capability to address challenging engineering problems. There is a need for scaling advanced analytics and for streamlined workflows in tackling big data problems. Using the example of an IoT based application that collects data from a fleet of connected cars and provides insight into their performance and health, this talk focuses on streamlined workflows for engineering data analytics. It covers a typical lambda architecture that operationalizes machine learning based algorithms. This real-world example also showcases the value of advanced algorithms and simulation in such applications.