Analytics and Big Data Machine Learning and Artificial Intelligence Blockchain Analytics Hadoop Azure Azure Data Platform Azure Cognitive Services Data Lake Modern Data Warehouse Data Management Data Science & AI Data Science Data Visualization Streaming Data Analytics Azure HDInsight
Turin, Piedmont, Italy
Andrea was co-founder and CTO of Ecube and CTO of Exage. He currentrly works as Chief Technical Officer at Value Partners defining mid and long term technology strategies focusing on data-driven digital transformation using Big Data and others data management technologies, Blockchain platfroms and Artificial Intelligence solutions.
In more than twenty years of hands-on experience in network management, information security, enterprise systems and data cloud, he gained expertise and consolidated competences readily applicable to innovative scenarios on Italian and international clients of different industries assisting them to empower the digital transformation process.
Andrea studied Computer Engineering at Politecnico di Torino.
Andrea è stato co-founder e CTO di Ecube e successivamente CTO di Exage. Attualmente lavora come Chief Technical Officer presso Value Partners definendo strategie tecnologiche di medio e lungo periodo nell'ambito della data-driven digital transformation utilizzando tecnologie tipiche degli scenari Big Data e più in generale di data management, piattaforme Blockchain e soluzioni di Artificial Intelligence.
In più di 20 anni di esperienza sul campo in ambito network management, information security, sistemi enterprise e soluzioni cloud, ha consolidato esperienze e competenze che tutt'oggi costituiscono la base per supportare scenari innovativi su clienti italiani e internazionali operanti in diversi settori assistendoli nel processo di digital transformation.
Andrea ha studiato Ingegneria Informatica al Politecnico di Torino.
The connected world creates a rate and volume of streaming cybersecurity data that is unprecedented, and attacks are increasingly sophisticated and multifaceted. Existing security tools typically provide one facet of cybersecurity info, but not even one was created for the big data generated by the digital world and it is unreasonably time-consuming to piece together data from multiple systems to assess the true nature of a single threat across an enterprise. A data-driven artificial intelligence approach enables information security teams to embark a cybersecurity journey to leverage big data to improved economics and improved threat detection. The key point is to create a single holistic view of enterprise risk that encompasses an expansive and contextual view of enterprise data to enable machine learning, real-time streaming analytics for accelerated threat detection and improved SOC efficiency. Rather than relying solely on internal IT staff, CISOs can use AI to process millions of events per second, a feat that would otherwise be impossible. But human expertise is still required: the goal should be to draw on the best of AI, take a consolidated view that bring people and tool together. At a time when the fear surrounding cybersecurity and automation is at an all-time high, take a deep breath and aim for a progressive approach to data-driven artificial intelligence approach, where the right technologies are applied at the right level.
Scenari architetturali nel mondo IoT: una panoramica su alcuni casi reali di implementazione