Extending Lakehouse Architecture with Collaborative Identity
Description
Lakehouse architecture has become a valuable solution for unifying data processing for AI, but faces limitations in maximizing data’s full potential. Additional data infrastructure is helpful for strengthening data consolidation and data connectivity with third-party sources, which are necessary for building full data sets for accurate audience modeling. In this session, LiveRamp will demonstrate to data and analytics decision-makers how to build on the Lakehouse architecture with extensions for collaborative identity graph construction, including how to simplify and improve data enrichment, data activation, and data collaboration. LiveRamp will also introduce a complete data marketplace, which enables easy, pseudonymized data enhancements that widen the attribute set for better behavioral model construction. With these techniques and technologies, enterprises across financial services, retail, media, travel, and more can safely unlock partner insights and ultimately produce more accurate inputs for personalization engines, and more engaging offers and recommendations for customers. Talk by: Erin Boelkens and Shawn Gilleran Here’s more to explore: A New Approach to Data Sharin…
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