Hosted by BDV PPP. BigDataStack, I-BiDaaS, Track & Know and Policy Cloud join forces in a series of online demonstrations of innovative Big Data Technologies unlocking the potential of various applications.

The new data-driven industrial revolution highlights the need for big data technologies to unlock the potential in various application domains. To this end, BDV PPP projects I-BiDaaS, BigDataStack, Track & Know and Policy Cloud deliver innovative technologies to address the emerging needs of data operations and applications. To fully exploit the sustainability and take full advantage of the developed technologies, the projects onboarded pilots that exhibit their applicability in a wide variety of sectors. In the Big Data Pilot Demo Days, the projects will showcase the developed and implemented technologies to interested end-users from the industry as well as technology providers, for further adoption.

One of the main goals of the I-BiDaaS project is to provide a Big Data as a self-service solution that will empower the actual employees of European companies in targeted sectors (banking, manufacturing, telecom), i.e., the true decision-makers, with the insights and tools they need in order to make the right decisions. In this big data pilot webinar, we will demonstrate in a step by step fashion the I-BiDaaS self-service solution and its application to the manufacturing sector. In more detail, we will present an overview of the I-BiDaaS project focusing on the requirements of the CRF pilot study, the I-BiDaaS architecture with its core technologies, and a step by step demo of the I-BiDaaS solution.

Whether you are a Big Data expert developer, a data analyst, or a non-IT specialist with the right domain knowledge, we will show how I-BiDaaS enables you to easily utilise and interact with big data technologies.





Introduction to the Big Data Pilot Demo series of webinars.

Despina Kopanaki – FORTH


Introduction to the I-BiDaaS project

Dusan Jakovetic – UNSPMF

14.10 – 14.20

CRF’s Pitches: Setting the requirements

Giuseppe Danilo Spennacchio – CRF


I-BiDaaS architecture: a Scientific & Technical view and how it addresses the requirements set by the CRF pilot study.

Dusan Jakovetic – UNSPMF


Step by Step demonstration of the I-BiDaaS solution and its application to the manufacturing sector.

Giuseppe Danilo Spennacchio – CRF


Introduction to the next webinar – Track & Know Insurance Sector: Using mobility data to understand and mitigate risky driving behaviour

Leonardo Longhi – Sistematica (Track & Know)



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Dr. Dusan Jakovetic is an Assistant Professor at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Serbia and he is also the I-BiDaaS Scientific & Technical Manager. He received the Ph.D. degree in electrical and computer engineering (ECE) from Carnegie Mellon University, Pittsburgh, PA, and Instituto de Sistemas e Robótica (ISR), Instituto Superior Técnico (IST), Lisbon, Portugal, in 2013. Since November 2015, he has been an Assistant Professor at the Department for Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Serbia. He works as a scientific and technical coordinator in several H2020 projects. His research interests include data analytics, optimization, and signal processing for distributed systems.

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Giuseppe Danilo Spennacchio holds a Master Degree in Chemical Engineering from the University Federico II of Naples, Italy. He started his career in the automotive sector, in planning and logistics. In 2015, he attained a Master in Automotive and joined the CRF as a manufacturing methodologies specialist, conducting research activities on lightweight material and adhesive bonding for automotive industry. In 2019, he changed role internally joining the operative group of Flexible and Adaptive Systems for manufacturing in the Factory Innovation Department. The main research activities are on flexible and adaptive manufacturing to optimize industrial processes and improve their quality. He participates in national and European projects as CRF technical support and coordinator.

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Leonardo Longhi graduated in Biomedical, Electronic and Communication Engineering at the Department of Applied Electronics at the Roma Tre University. His M.Sc. thesis was about Pattern Recognition methods for ML applications to recognize drowsiness and lack of focus by analyzing facial expressions. He has also been collaborating in developing businesses for Italian start-ups until 2016 in biomedical applications and in the signal processing business area. Afterwards he shifted to applied informatics in insurance and telematics products. He is currently working as a consultant for one of the most important telematics companies in Europe.