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Breaking Data Silos: AI-Ready Data Strategies with Nishith Trivedi, Enterprise Data Governance and Global MDM Lead at Pfizer
Manage episode 471825340 series 3451197
محتوای ارائه شده توسط Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Michael Burke and Chris Detzel, Michael Burke, and Chris Detzel یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
In this insightful episode of Data Hurdles, hosts Chris Detzel and Michael Burke sit down with Nishith Trivedi, Enterprise Data Governance and Global MDM Lead at Pfizer. Nishith shares his journey from chemical engineering to becoming a data expert, and details how his team is transforming Pfizer's data landscape to support AI initiatives.
Nishith provides a fascinating look at how a pharmaceutical giant manages data across multiple verticals—from supply chain to R&D—while explaining the challenges of making data "AI-ready." He discusses the evolution from vector-based RAG to graph-based approaches, the importance of ontologies in preventing AI hallucinations, and how knowledge graphs help connect unstructured data.
The conversation explores how Pfizer is navigating complex regulatory requirements across 150+ countries, the shift toward patient-centric approaches, and the vision for creating FAIR data (Findable, Accessible, Interoperable, and Reusable). Listeners will gain valuable insights into enterprise data governance, the future of agentic AI, and practical strategies for breaking down data silos in large organizations.
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