Building a Highly Effective People Analytics Team at Barclays | Jésus Rogel-Salazar, Barclays Building a Highly Effective People Analytics Team at Barclays | Jésus Rogel-Salazar, Barclays
EGG AMS 2019 Opening Plenary | Hylke Visser, Dataiku EGG AMS 2019 Opening Plenary | Hylke Visser, Dataiku
The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM
Data, a factor of CRM transformation | Remi Mathieu & Alexis Miginiac, SNCF Data, a factor of CRM transformation | Remi Mathieu & Alexis Miginiac, SNCF
Augmented Human Intelligence | Walid Mehanna, Daimler Augmented Human Intelligence | Walid Mehanna, Daimler
Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku
Data Science Pioneers: Conquering the Next Frontier | Romain Doutrioux, Dataiku Data Science Pioneers: Conquering the Next Frontier | Romain Doutrioux, Dataiku
Cleaner Oceans Through AI and Data Science | Bruno Sainte-Rose, The Ocean Cleanup Cleaner Oceans Through AI and Data Science | Bruno Sainte-Rose, The Ocean Cleanup
KI 2.0: KI bei Non-Tech Unternehmen | Alexander Thamm, Alexander Thamm GmbH KI 2.0: KI bei Non-Tech Unternehmen | Alexander Thamm, Alexander Thamm GmbH
Transformation data chez Engie GEM | Haga Rabekoto, ENGIE Transformation data chez Engie GEM | Haga Rabekoto, ENGIE
How to reposition a data mining team in a data center of excellence | Arnaud Foujols, Monoprix How to reposition a data mining team in a data center of excellence | Arnaud Foujols, Monoprix
Von der Automatisierung zur Autonomie: Wie kann KI die Transformation unterstützen? | Jan R. Seyler, Festo AG & Co. KG Von der Automatisierung zur Autonomie: Wie kann KI die Transformation unterstützen? | Jan R. Seyler, Festo AG & Co. KG
How Mercedes-Benz, Vodafone, and Credit Suisse Super-Sized their Data Initiatives | A Panel How Mercedes-Benz, Vodafone, and Credit Suisse Super-Sized their Data Initiatives | A Panel
AI et Data à l’UNICEF – Pour Quelles Innovations? | Hubert Chaminade, UNICEF AI et Data à l’UNICEF – Pour Quelles Innovations? | Hubert Chaminade, UNICEF
Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext
Diversity and Inclusion in Data Science | Noelle Silver, HackerU Diversity and Inclusion in Data Science | Noelle Silver, HackerU
Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop
The Data Science Food Chain | Shaun McGirr, Dataiku The Data Science Food Chain | Shaun McGirr, Dataiku
Quelle place occupe la data au sein du Groupe La Poste | Pierre-Etienne Bardi, Groupe La Poste Quelle place occupe la data au sein du Groupe La Poste | Pierre-Etienne Bardi, Groupe La Poste
The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup
Ethics, Data Science, and Public Service Media | Ben Fields, BBC News Ethics, Data Science, and Public Service Media | Ben Fields, BBC News
Le revenue management augmenté par l’IA | Benjamin Lalanne, Groupe Air France Le revenue management augmenté par l’IA | Benjamin Lalanne, Groupe Air France
From Silos to Self-Service: Data Transformation at GE Aviation | Jon Tudor, GE Aviation From Silos to Self-Service: Data Transformation at GE Aviation | Jon Tudor, GE Aviation
How to Make a Success of Data Science | Jan Teichmann, Zoopla How to Make a Success of Data Science | Jan Teichmann, Zoopla
