Session: Localizing in the world of global operations
Working with data teams before and AI teams now, the common thread has always been: standardize and centralize to enable analytics, insights, data products, and AI. I was deep into this path, building infrastructures meant to centralize, scale, and power enterprise-wide capabilities.
Then data localization hit.
Working for a truly global business with shared systems and processes for cost optimization, I faced a critical question: how do we decouple people, technology, and process all at once without breaking a successful business that depends on all three pillars?
In this session, I'll share the lessons I learned and the framework built to stay compliant while maintaining business continuity. You'll learn how to architect for geographic requirements without sacrificing centralization—and what actually happens to your AI when borders fragment your data.
My framework includes laying the foundational steps and getting compliant efficiently through a layered approach.
The foundational layer starts with data—introspection from data cataloging to understanding data flows. What data do you have? Where does it live? Where does it move?
The next layer uncovers the processes—where does data get transformed, where are the storage points, who interacts with it, and critically, which AI models are consuming it?
The final layer is technology, viewed through the lens of what can be retained and reused. What infrastructure is portable? What creates vendor lock-in?
Then the puzzle starts to take shape. The outcomes of these three layers help you define a cloud-agnostic, vendor-agnostic, compliant data platform that can continue powering local businesses while keeping AI dreams alive for global organizations.
Now, as more countries view their digital infrastructure and citizen data as sovereign assets to protect, this same formula can be quickly replicated without massive disruption or excessive costs. You're not starting from scratch each time—you're applying a proven framework that scales geographically while maintaining the centralization benefits that make modern data and AI possible.
Bio
With more than 20 years of data expertise, Sangeetha Parsan is an expert in designing and implementing data and technology solutions, as well as data integration solutions for B2B organizations. She currently heads a vibrant team of data experts focused on seamlessly integrating businesses onto data platforms, particularly in complex corporate mergers and acquisitions. Sangeetha is driven by a passion for connecting data with business requirements, ensuring that solutions are not only inventive but also practical and user-focused. She has an in-depth comprehension of data's role including harnessing of data for predictive and prescriptive applications that drive informed decisions.
Her motivation is to share the cutting edge technical expertise and practical delivery aspects that will make a data initiative successful in today's value based business world.