Arvind Hosagrahara, MathWorks
As big data frameworks mature, solutions built around these technologies provide an increased capability of addressing 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.
This presentation was delivered at Big Data Spain 2017.