DP-800T00: Develop AI-enabled database solutions Training

Design and implement database objects with SQL

• Introduction
• Understand your SQL Server-based platform choices
• Build effective tables
• Optimize with indexes
• Use specialized table types
• Enforce data integrity with constraints
• Manage JSON columns and indexes
• Partition tables for scale
• Exercise - Create and maintain database objects

Implement programmability objects with SQL

• Introduction
• Create views
• Create stored procedures
• Create scalar functions
• Create table-valued functions
• Create triggers
• Choose when to use each option
• Exercise: Implement programmability objects in SQL Server

Write advanced T-SQL code

• Introduction
• Organize queries with Common Table Expressions
• Apply window functions for analytics
• Process JSON data with built-in functions
• Match patterns with regular expressions
• Find approximate matches with fuzzy string functions
• Traverse relationships with graph queries
• Compare rows with correlated subqueries
• Handle errors with TRY...CATCH
• Exercise - Work with JSON functions

Implement SQL solutions using AI-assisted tools

• Introduction
• Describe AI-assisted development tools available for Microsoft SQL platforms
• Interpret security impact of using AI-assisted tools
• Enable GitHub Copilot and Fabric Copilot
• Configure model and Model Context Protocol (MCP) tool options
• Create and configure GitHub Copilot instruction files
• Connect to MCP server endpoints (SQL Server and Fabric Lakehouse)
• Exercise - Configure AI-assisted tools for database development

Implement data security and compliance with SQL

• Introduction
• Protect data with encryption
• Configure dynamic data masking
• Implement row-level security
• Manage permissions and secure access
• Implement auditing
• Configure secure access to AI services
• Secure data API endpoints
• Exercise: Implement security features

Optimize database performance

• Introduction
• Recommend database configurations
• Preserve data integrity with transaction isolation levels and concurrency controls
• Evaluate query performance with execution plans and DMVs
• Monitor and tune queries with Query Store and Query Performance Insight
• Identify and resolve blocking and deadlocks
• Exercise: Optimize query performance

Implement CI/CD by using SQL Database Projects

• Introduction
• Create, build, and validate SQL Database Projects
• Configure source control and manage reference data
• Manage branching, pull requests, and conflict resolution
• Detect and resolve schema drift
• Implement CI/CD pipelines
• Design and implement a testing strategy
• Exercise: Implement CI/CD by using SQL Database Projects

Integrate SQL solutions with Azure services

• Introduction
• Create configuration files for Data API Builder
• Define entities for REST and GraphQL
• Expose database objects, stored procedures, and views
• Explore deployment options for Data API Builder
• Recommend Azure Monitor configurations
• Handle changes with event-driven patterns
• Exercise - Configure Data API Builder for a product catalog

Design and implement models and embeddings with SQL

• Introduction
• Understand and evaluate models for SQL database workloads
• Create and manage external models in SQL
• Design embeddings for SQL database workloads
• Generate and maintain embeddings for SQL database workloads
• Exercise - Generate and update embeddings in Azure SQL Database

Design and implement intelligent search with SQL

• Introduction
• Choose an intelligent search approach
• Implement full-text search
• Prepare SQL for vector search
• Implement vector search query patterns
• Implement hybrid search and ranking
• Exercise - Implement intelligent search with full-text, vector, and hybrid queries

Design and implement RAG with SQL

• Introduction
• Identify RAG use cases and architecture
• Prepare retrieval context for augmentation
• Augment prompts with database context
• Generate and process RAG responses
• Exercise: Implement a RAG solution