
Data drives innovation, yet many organizations struggle with siloed systems. This session focuses on how to build intelligent data architectures that not only provide valuable business insights but also enable Generative AI. We'll explore how to transition from siloed data to cohesive, AI-ready data products. Discover practical strategies for designing scalable and modular data architectures, optimizing metadata for AI, and overcoming the challenges of integration and scaling in complex enterprises.
Key Topics:
Speaker: Lakshmi Isukapally

Lakshmi is Vice President - Principal Architect, Data Architecture, at American Express. Lakshmi is responsible for the Data Architecture practice and for consistent data architecture across all critical data domains, Enterprise Data Management, and tooling for automated data risk mitigation, for consistent data architecture across critical data domains. Her domain expertise includes Data Architecture and Data engineering Technologies (SQL & NoSQL, Vector DB databases, streaming platforms), Data Management, Distributed Systems Architecture and Design, Microservices Architecture, Event-Driven Design, Machine Learning Engineering, and Cloud Platforms.
Speaker: Shoma Chakravarty

As a Chief Architect at American Express, Shoma specializes in marketing, personalization, omnichannel orchestration, and Identity and Access Management. Previously, she was the Vice President of Enterprise Architecture, Cloud Platforms, and Governance at Verizon, where she created Verizon’s first-ever Enterprise Architecture function and helped to shape a multi-cloud strategy. Prior to joining Verizon, she was the Technical Leader (CTO) for the Telecom division at Amazon Web Services (AWS), where she developed the technical strategy, as well as the product and technical field execution roadmap for accelerating AWS’s adoption in Telecom. Previously, she held senior technology roles at Telarix, Inc. and IBM.
In her spare time, she enjoys hiking, nature, listening to music, and cooking.
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