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webinar

How Delphix can drive Machine Learning & AI

Watch this webinar where Ugo Pollio will explain how Delphix can help accelerate AI initiatives by bringing all the relevant data to your training models.

Watch this webinar where Ugo Pollio will explain how Delphix can help accelerate AI initiatives by bringing all the relevant data to your training models and decoupling the Machine Learning pipeline into parallel streams.

Ugo will show how:

  • Delphix can reduce the cost of AI/ML projects

  • Delphix ensures that sensitive data is secured for use by Data Scientists & Analysts in their AI/ML projects

  • Delphix can help you bridge your multi-cloud or on-prem data sources and datasets seamlessly, and increase the speed of innovation.

Ugo Pollio

Field CTO EMEA, Delphix

Ugo a plus de 20 ans d’expérience dans le secteur ICT et a occupé plusieurs postes. Il a travaillé chez Delphix pendant plus de 8 ans en tant Solution Engineer, manager et directeur Customer Success. Alimenté par la curiosité, notamment pour les technologies, il est le Chief Technology Officer dans la région EMEA. Il collabore avec nos clients pour établir une vision stratégique et une roadmap communes, en veillant à ce que les clients tirent le meilleur parti de leur investissement Delphix.

Chay Thornhill

Chay has +25 years of experience as a technical creative leader with expertise in providing innovative data solutions to address application data bottlenecks. He worked at IBM for 11 years, and then for a number of leading investment banks. He managed the Data Services team at Fidelity International, focusing on the availability of Production data, when he discovered Delphix.  He wrote the business case, gained approval and managed the implementation of Delphix at Fidelity. The Delphix Data Platform has developed into an intelligent solution enabling digital transformation, and now Chay manages the Solutions Engineering team at Delphix. Having been a customer he has a great view of how companies can help accelerate application development whilst removing data bottlenecks.