Bootstrapping Data Analytics Pipelines in Industrial Projects

13 May 2022
Start time 
11:30 am
Polo Ferrari 2 - Via Sommarive 9, Povo (Trento)
Seminar Room
Target audience: 
UniTrento students
Contact person: 
Prof. Matteo Brunelli
Contact details: 
Dipartimento di Ingegneria Industriale
Jyrki Savolainen, School of Business and Management, LUT University, Finland


Data-based algorithms and machine learning (ML) algorithms, such as deep learning and neural networks, are finding their way into industrial applications. However, the possibilities for organizations to effectively implement these, and other state-of-the-art, methods on top of raw data in their ML-pipelines are seldom addressed. This is because the central interest of the researchers is most often on the theoretical development of methods using ready-made, clean and curated datasets. In this seminar, an illustrative example of an industrial-scale data-analytics development project is presented and discussed to illustrate some of the practical challenges of data-analytics implementation.