Real-time data has become a non-negotiable foundation for powering machine learning (ML) and generative AI (GenAI). From delivering event-driven predictions to powering live recommendations and dynamic chatbot conversations, AI/ML initiatives depend on the continuous movement, transformation, and synchronization of diverse datasets across clouds, applications, and databases.
But complexity stands in the way: incompatible platforms, brittle pipelines, fragmented architectures, and the growing pressure of data privacy and compliance risks make it challenging for teams to deliver trusted, real-time data to models and applications.
In this webinar with BARC, a leading analyst firm for data & analytics and enterprise software, you’ll learn how to overcome these challenges and build the data backbone for AI/ML success.
Join us to:
Break down the key elements of modern data streaming architectures and their impact on AI/ML.
Define the must-have characteristics of a data streaming architecture.
Explore real-world use cases, including streaming ELT for experimentation, real-time ML, and retrieval-augmented generation (RAG) for GenAI.
Gain actionable guidance to build scalable, resilient streaming pipelines that drive continuous innovation and measurable value.
Executives and practitioners leading data and AI transformation — learn what it takes to stay competitive. Register today!
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