Integrating Azure SQL and OpenAI represents a significant leap in data analytics, particularly with the incorporation of vector databases. These databases are pivotal in identifying similarities across diverse data types, making them essential for semantic search and recommendation systems applications. The private preview of Vector Support in Azure SQL underscores Microsoft's commitment to innovation, providing a seamless experience for developers to leverage these capabilities.

In this session, you will learn:

1. Embedding Data with Python: How to embed your data into vectors using Python and store these vectors in your Azure SQL database.

2. Connecting to Azure OpenAI from SQL: This section explains how to connect Azure OpenAI with SQL within Azure SQL, enabling advanced data processing and insights.

3. Vector Similarity Search Application: Demonstrate an application that performs vector similarity searches within an Azure SQL database, showcasing real-world use cases and efficiency.

We will share all resources, including the application and source code. This session will equip you with the knowledge and tools to enhance your data analytics projects using the powerful combination of Azure SQL and Azure OpenAI.

Attendees should have a basic knowledge of SQL and Python and an active Azure subscription, with access to Azure SQL Database and Azure OpenAI services. This session is ideal for data analysts, data scientists, AI developers, database administrators, and technology enthusiasts.