Implementing Vector Search in Your Application with SQL Server 2025 | Data Exposed: MVP Edition

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Going a level deeper than a basic semantic search talk, we’ll explore semantic search, how to implement it in your app, and how to ingest data at scale to support your application’s AI needs. Chapters: 0:00 Introduction 3:50 Demo ✅ Resources: VECTOR_SEARCH (Transact-SQL) (Preview): https://learn.microsoft.com/en-us/sql/t-sql/functions/vector-search-transact-sql?view=sql-server-ver17 Vector search and vector indexes in the SQL Database Engine: https://learn.microsoft.com/en-us/sql/sql-server/ai/vectors?view=sql-server-ver17 Github: https://github.com/Azure-Samples/azure-sql-db-vector-search About Joseph D'Antoni: Joseph D'Antoni is a Principal Consultant at Denny Cherry and Associates Consulting. He is recognized as a VMWare vExpert and a Microsoft Data Platform MVP, and has over 20 years of experience working in both Fortune 500 and smaller firms. He has worked extensively on database platforms and cloud technologies and has specific expertise in performance tuning, infrastructure, and disaster recovery. About MVPs: Microsoft Most Valuable Professionals, or MVPs, are technology experts who passionately share their knowledge with the community. They are always on the "bleeding edge" and have an unstoppable urge to get their hands on new, exciting technologies. They have very deep knowledge of Microsoft products and services, while also being able to bring together diverse platforms, products and solutions, to solve real world problems. MVPs make up a global community of ov

Published 2025-10-27 · Watch on YouTube ↗
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