Data teams face pressure to deliver real-time business insights across finance, supply chain, HR, and beyond. They need apps that are fueled with AI recommendations and insights available in business terms. The key lies in adopting a business data fabric architecture that interoperates across multi-cloud landscapes. SAP’s data and analytics solutions serve as the foundation for this data fabric, delivering an integrated, semantically-rich data layer that ensures seamless and scalable access to data without duplication. Join us to learn how to build this crucial foundation for your AI applications.
talk-data.com
Speaker
Marc Geall
2
talks
SVP Head of Product, Technology & Experience, Data & Analytics - SAP
SAP
Marc is a senior executive at SAP with the current responsibility as Head of Product, Technology & Experience of SAP’s Data & Analytics development organisation, and has held multiple roles for SAP BTP since 2012. He is also on the Advisory Board of SEDNA. Marc has split his career between the software industry and financial services. In software he has been Chief Strategy Officer at SAP and Autonomy, and held other leadership roles across sales, development, and corporate functions. In financial services, Marc led the Technology and TMT research practices for Citigroup and Deutsche Bank respectively, where he was the top ranked sell-side financial analyst for many years. Marc has a Master’s degree in Engineering from Cambridge University.
Bio from: Big Data LDN 2024
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Talks & appearances
2 activities · Newest first
with
Parul Mishra
,
Anupam Datta
,
Mike Ferguson
(Big Data LDN)
,
Rahul Pathak
,
Stijn 'Stan' Christiaens
(Collibra)
,
Marc Geall
(SAP)
In this flagship Big Data LDN keynote debate, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, how to manage, produce, share and govern data and AI, and issues on-the-horizon that companies should be planning for today.
Attendees will learn best practices for data and analytics implementation in a modern data-driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.