Hiding Apache Spark Complexity for Fast Prototyping of Big Data Applications—Industry 4.0 and Logistics Success Examples

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In many cases, Big Data becomes just another buzzword because of the lack of tools that can support both the technological requirements for developing and deploying of the projects and/or the fluency of communication between the different profiles of people involved in the projects.
In this talk, we will present Moriarty, a set of tools for fast prototyping of Big Data applications that can be deployed in an Apache Spark environment. These tools support the creation of Big Data workflows using the already existing functional blocks or supporting the creation of new functional blocks. The created workflow can then be deployed in a Spark infrastructure and used through a REST API.

For better understanding of Moriarty, the prototyping process and the way it hides the Spark environment to the Big Data users and developers, we will present it together with a couple of examples based on a Industry 4.0 success cases and other on a logistic success case.

Session hashtag: #EUent6

About Francisco J. Lacueva

Francisco J. Lacueva got his Mr. in Computer Engineer from the University of Zaragoza on 2000. He works for ITAINNOVA since 2004. Here collaborated in different R&D projects such as Virtual e-Health, Telco, Tourism and Supply Change Management public and private founded. Before working for ITA, he worked in ATOS between 1999 and 2002, Alerce Informatica Aplicada (2002-2004). He is actually working in the ITC-Big Data and Cognitive Systems knowledge area of ITAINNOVA where he is collaborating in different projects. In particular he is coordinating ITAINNOVA activities in FACTS4WORKER H2020 founding project.