Enhancing SQL Development in VS Code with GitHub Copilot and Microsoft Fabric
Microsoft Developer presents a Data Exposed episode featuring Anna Hoffman and Carlos Robles, highlighting the new GitHub Copilot integration in the MSSQL extension for VS Code and showcasing how AI, containers, and Microsoft Fabric modernize SQL development.
Enhancing SQL Development in VS Code with GitHub Copilot and Microsoft Fabric
Presenters: Anna Hoffman, Carlos Robles
Overview
This episode explores advancements in SQL development using Visual Studio Code (VS Code) and the MSSQL extension, focusing on the integration of GitHub Copilot and new deployment options with Microsoft Fabric.
Key Topics
1. GitHub Copilot Integration
- Ask and Agent Modes: Demonstrates GitHub Copilot's ability to assist in writing and optimizing SQL queries directly in VS Code, leveraging both Ask and Agent capabilities for intelligent, context-aware suggestions.
- Productivity Gains: Highlights how AI-assisted coding accelerates routine tasks, improves code accuracy, and helps developers adopt best SQL practices.
- Agent Tools and Slash Commands: Introduces tools and shortcuts that automate frequent actions, reducing manual steps in the development workflow.
2. Efficient SQL Environment Provisioning
- SQL Server Containers: Quick demos on provisioning local SQL Server containers for isolated, flexible development and testing.
- Microsoft Fabric Deployments: Showcases smooth deployment workflows targeting SQL databases in Microsoft Fabric, enhancing scalability and integration within the Azure ecosystem.
Getting Started
Recommended Channels & Social
- Twitter: Anna Hoffman, Carlos Robles, Azure SQL
- YouTube: Data Exposed, Microsoft Azure SQL, Microsoft SQL Server, Microsoft Developer
Additional Resources
- Learn more about using AI and automation in SQL Server environments
- Explore deploying and managing cloud-scale databases with Fabric and Azure SQL
This episode offers demonstrations and practical insights to help developers modernize their SQL workflows by blending AI-powered assistance and cloud-native deployment patterns.