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Saar Gillis

Saar Gillis is a Data Solution Architect @ Cegeka. Working with the Microsoft BI suite since 2000. Saar has been involved in all different aspects of Business Intelligence implementations:

requirements & source analysis, dimensional modeling, database design, ETL development and report development.





Presenting

Real-time predictive maintenance with Azure ML Studio & PowerBI

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In this session, racing data (a toy dataset) will be used to demonstrate how predictive maintenance can be implemented with an end-to-end Microsoft Azure solutions. First, data from car sensors will be ingested into Azure with Event Hubs. Using Streaming analytics and Azure ML Studio, we'll predict when a car needs a tire change in real-time. The engineers of a racing team can confirm or deny the prediction in a Power BI report with Power Apps, which can be used to further train the AI algorithm.

Breght Van Baelen  400