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Purpose of this document
This study guide should help you understand what to expect on the exam and includes a summary of the topics the exam might cover and links to additional resources. The information and materials in this document should help you focus your studies as you prepare for the exam.
| Useful links | Description |
|---|---|
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About the exam
Languages
Some exams are localized into other languages, and those are updated approximately eight weeks after the English version is updated. If the exam isn't available in your preferred language, you can request an additional 30 minutes to complete the exam.
Note
The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam.
Note
Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used.
Skills measured as of March 12, 2026
Audience profile
As a candidate for this Microsoft Certification, you should have subject matter expertise in designing and developing AI-enabled database solutions across Microsoft SQL platforms, including Microsoft SQL Server, Azure SQL, and SQL databases in Microsoft Fabric.
You should also have experience writing T-SQL code and developing databases in Microsoft SQL platforms. Plus, you need to be familiar with continuous integration and continuous deployment (CI/CD) practices in GitHub, AI-assisted development tools, and AI concepts, such as embeddings, vectors, and models.
Your responsibilities include:
Designing and developing database solutions that include both structured and semi-structured data.
Integrating AI features into modern and highly scalable enterprise applications.
Securing, optimizing, and deploying database solutions.
Implementing AI capabilities in database solutions.
You work closely with application developers; database administrators (DBAs); architects; AI engineers; development, security, operations (DevSecOps) engineers; security and compliance administrators; and other stakeholders to deliver robust, high-performance database solutions that power modern applications and AI-driven experiences.
Skills at a glance
Design and develop database solutions (35–40%)
Secure, optimize, and deploy database solutions (35–40%)
Implement AI capabilities in database solutions (25–30%)
Design and develop database solutions (35–40%)
Design and implement database objects
Design and implement tables, including data types, size, columns, indexes, and column store indexes
Design and implement specialized tables, including in-memory, temporal, external, ledger, and graph
Design and implement JSON columns and indexes
Design and implement database constraints, including PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, and DEFAULT
Design and implement SEQUENCES
Design and implement partitioning for tables and indexes
Implement programmability objects
Create views
Create scalar functions
Create table-valued functions
Create stored procedures
Create triggers
Write advanced T-SQL code
Write common table expressions (CTEs)
Write queries that include window functions
Write queries that include JSON functions, such as JSON_OBJECT, JSON_ARRAY, JSON_ARRAYAGG, JSON_CONTAINS, OPENJSON, and JSON_VALUE
Write queries that include regular expressions, such as REGEXP_LIKE, REGEXP_REPLACE, REGEXP_SUBSTR, REGEXP_INSTR, REGEXP_COUNT, REGEXP_MATCHES, and REGEXP_SPLIT_TO_TABLE
Write queries that include fuzzy string matching functions, such as EDIT_DISTANCE, EDIT_DISTANCE_SIMILARITY, and JARO_WINKLER_DISTANCE
Write graph queries that use the MATCH operator
Write correlated queries
Implement error handling
Design and implement SQL solutions by using AI-assisted tools
Interpret security impact of using AI-assisted tools
Enable GitHub Copilot and Microsoft Copilot in Fabric
Configure model and Model Context Protocol (MCP) tool options in a GitHub Copilot or Copilot in Fabric chat session
Create and configure GitHub Copilot instruction files
Connect to MCP server endpoints, including Microsoft SQL Server and Fabric lakehouse
Secure, optimize, and deploy database solutions (35–40%)
Implement data security and compliance
Design and implement data encryption, including Always Encrypted and column-level encryption
Design and implement Dynamic Data Masking
Design and implement Row-Level Security (RLS)
Design and implement object-level permissions
Implement secure database access, including passwordless
Implement auditing
Secure model endpoints, including Managed Identity
Secure GraphQL, REST, and MCP endpoints
Optimize database performance
Recommend database configurations
Preserve data integrity and consistency by using transaction isolation levels and concurrency controls
Evaluate query performance by using query execution plans, dynamic management views (DMVs), Query Store, and Query Performance Insight
Identify and resolve query performance issues, including blocking and deadlocks
Implement CI/CD by using SQL Database Projects
Design and implement a testing strategy, including unit tests and integration tests
Create and manage reference/static data in source control
Create, build, and validate database models by using SQL Database Projects, including SDK-style models
Configure source control for SQL Database Projects
Manage branching, pull requests, and conflict resolution
Implement secrets management
Detect schema drift by using SQL Database Projects
Update an SQL database project and deploy changes
Design and implement controls for deployment pipelines, including branching policies, triggers in approvals, authentication tables, and code owners
Integrate SQL solutions with Azure services
Create configuration files for Data API builder (DAB)
Configure entities for REST and GraphQL, including data caching, pagination, searching, and filtering
Configure REST or GraphQL endpoints
Expose database objects, stored procedures, and views, including GraphQL relationships
Configure and implement DAB deployment
Recommend Azure Monitor configurations, including Application Insights and Log Analytics
Handle changes by using change event streaming (CES), change data capture (CDC), Change Tracking, Azure Functions with SQL trigger binding, or Azure Logic Apps
Implement AI capabilities in database solutions (25–30%)
Design and implement models and embeddings
Evaluate external models, including multimodal, multilanguage, sizes, and structured output
Create and manage external models
Choose an embedding maintenance method, including table triggers, Change Tracking, Azure Functions with SQL trigger binding, Azure Logic Apps, CDC, CES, and Microsoft Foundry
Identify which columns to include in embeddings
Design and implement chunks for embeddings
Generate embeddings
Design and implement intelligent search
Choose from full-text, semantic vector, and hybrid search
Implement full-text search
Design for vector data, including vector data type, vector indexes, and size
Identify when to use vector-related types and functions for semantic searching, including VECTOR_NORMALIZE, VECTOR_DISTANCE, VECTORPROPERTY, and VECTOR_SEARCH
Choose between using ANN and ENN for vector search
Evaluate vector index types and metrics
Implement vector search
Implement hybrid search
Implement reciprocal rank fusion (RRF)
Evaluate performance of vector and hybrid search
Design and implement retrieval-augmented generation (RAG)
Identify use cases for RAG
Create a prompt by using the sp_invoke_external_rest_endpoint stored procedure
Convert structured data to JSON for language model processing
Send results to language model
Extract language model responses
Study resources
We recommend that you train and get hands-on experience before you take the exam. We offer self-study options and classroom training as well as links to documentation, community sites, and videos.
| Study resources | Links to learning and documentation |
|---|---|
| Get trained | Choose from self-paced learning paths and modules or take an instructor-led course |
| Find documentation | Microsoft Fabric Microsoft SQL |
| Ask a question | Microsoft Q&A | Microsoft Docs |
| Get community support | SQL Server Blog - Community Hub Microsoft Fabric Blog |
| Follow Microsoft Learn | Microsoft Learn - Microsoft Tech Community |
| Find a video | Exam Readiness Zone Data Exposed Browse other Microsoft Learn shows |