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Microsoft DP-800 Exam Syllabus Topics:

SectionWeightObjectives
Implement AI capabilities in database solutions25-30%- Use AI-assisted development tools
  • 1. Leverage AI tools for T-SQL development
  • 2. Validate and test AI-enhanced solutions
- Build intelligent search and retrieval
  • 1. Optimize search performance and relevance
  • 2. Implement semantic search and RAG patterns
  • 3. Design and implement embedding pipelines
- Integrate AI models and services
  • 1. Create and manage external models
  • 2. Implement vector data and embeddings
  • 3. Integrate with Azure AI services and Microsoft Foundry
Design and develop database solutions35-40%- Design database solutions
  • 1. Design solutions for structured and semi-structured data
  • 2. Design for maintainability and DevOps integration
  • 3. Design for scalability and performance
- Develop database solutions
  • 1. Write and optimize T-SQL code
  • 2. Implement database objects and structures
  • 3. Implement data integration and transformation
Secure, optimize, and deploy database solutions35-40%- Secure database solutions
  • 1. Implement authentication and authorization
  • 2. Implement compliance and auditing
  • 3. Protect data at rest and in transit
- Deploy and maintain solutions
  • 1. Deploy across SQL Server, Azure SQL, and Microsoft Fabric
  • 2. Manage updates and versioning
  • 3. Implement CI/CD for databases
- Optimize performance and reliability
  • 1. Optimize queries and indexes
  • 2. Monitor and troubleshoot performance
  • 3. Ensure high availability and disaster recovery

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Microsoft Developing AI-Enabled Database Solutions Sample Questions (Q39-Q44):

NEW QUESTION # 39
You have a SQL database in Microsoft Fabric that contains a nvarchar (max) column named MessageText. An ID is always contained within the first paragraph of MessageText.
You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText.
What should you include in the query?

Answer: C

Explanation:
To extract an ID (e.g., alphanumeric) from the first paragraph of an nvarchar(max) column in Microsoft Fabric using STRING_ESCAPE, use STRING_SPLIT or CHARINDEX to isolate the first paragraph, apply STRING_ESCAPE, and a regex pattern.
Note: T-SQL does not natively support a REGEXP_SUBSTR function like Oracle/Snowflake. The solution below uses STRING_ESCAPE followed by pattern matching via PATINDEX and SUBSTRING to extract a typical alphanumeric ID.
Reference:
https://learn.microsoft.com/en-us/sql/t-sql/queries/contains-transact-sql


NEW QUESTION # 40
You need to create a table in the database to store the telemetry data. You have the following Transact-SQL code.

Answer:

Explanation:

Explanation:

The first statement is No . The requirement says telemetry data must be stored in a partitioned table to provide predictable performance for ingestion and retention operations. However, the shown CREATE TABLE statement does not define a partition function or partition scheme, and the table is created with a regular clustered primary key on TelemetryId. Microsoft's partitioning guidance states that creating a partitioned table requires a partition function , a partition scheme , and creating the table or index on that partition scheme using a partitioning column. None of that appears in the code, so the table is not partitioned.
The second statement is Yes . The code creates a JSON index named JI_VehicleTelemetry_Location on LocationJson for these specific JSON paths: $.location.latitude, $.location.longitude, and $.location.accuracy.
That matches the requirement that those JSON properties must be filterable by using an index seek .
Microsoft documents that JSON indexing is used to optimize filtering and sorting on JSON properties, and the index only helps for the properties included in the index definition.
The third statement is No . The JSON index is defined only for latitude, longitude, and accuracy. A query filtering on $.location.heading references a different path that is not included in the index definition, so that query would not use JI_VehicleTelemetry_Location for that predicate. JSON indexes are path-specific; they do not automatically cover unrelated properties in the same JSON document.


NEW QUESTION # 41
Drag and Drop Question
You have an Azure SQL database named SalesDB that contains tables named Sales.Orders and Sales.OrderLines. Both tables contain sales data.
You have a Retrieval Augmented Generation (RAG) service that queries SalesDB to retrieve order details and passes the results to a large language model (LLM) as JSON text. The following is a simple of the JSON.

You need to return one JSON document per order that includes the order header fields and an array of related order lines. The LLM must receive a single JSON array of orders, where each order contains a lines property that is a JSON array of line items.
Which Transact-SQL commands should you use to produce the required JSON shape from the relational tables? To answer, drag the appropriate commands to the correct operations. Each command may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 42
You have a Microsoft SQL Server 2025 instance that contains a database named SalesDB.
SalesDB supports a Retrieval Augmented Generation (RAG) pattern for internal support tickets.
The SQL Server instance runs without any outbound network connectivity.
You plan to generate embeddings inside the SQL Server instance and store them in a table for vector similarity queries.
You need to ensure that only a database user account named AIApplicationUser can run embedding generation by using the model.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: D,E

Explanation:
To implement a Retrieval Augmented Generation (RAG) pattern in an isolated SQL Server 2025 instance, you can use the new native vector capabilities to generate, store, and query embeddings without needing outbound internet access.
[E] 1. Enable External REST Endpoints
Because your instance is isolated, you must first enable the configuration that allows SQL Server to communicate with your internal Microsoft Foundry (or local) endpoint.
EXEC sp_configure 'external rest endpoint enabled', 1;
RECONFIGURE;
2. Create the External Model Project
Register your Microsoft Foundry REST endpoint as an external model. This allows SQL Server to treat the internal service as a registered provider for generating embeddings.
[C] 3. Grant Permission to a Specific User
To restrict embedding generation to a single specific database user, grant the EXECUTE permission on the newly created external model.
-- Granting EXECUTE only to the specific user 'AppUser'
GRANT EXECUTE ON EXTERNAL MODEL::[MyFoundryEmbeddingModel] TO [AppUser]; Use code with caution.
4. Generate and Store Embeddings
Use the AI_GENERATE_EMBEDDINGS function to process text into vectors and store them in a table with the new VECTOR data type.
Reference:
https://www.red-gate.com/simple-talk/databases/sql-server/sql-server-2025-create-external- model-and-ai_generate_embeddings-commands-explained/


NEW QUESTION # 43
You have a Microsoft SQL Server 2025 instance that contains a database named SalesDB SalesDB supports a Retrieval Augmented Generation (RAG) pattern for internal support tickets. The SQL Server instance runs without any outbound network connectivity.
You plan to generate embeddings inside the SQL Server instance and store them in a table for vector similarity queries.
You need to ensure that only a database user account named AlApplicationUser can run embedding generation by using the model.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: D,E

Explanation:
Because the SQL Server 2025 instance has no outbound network connectivity , the embedding model cannot rely on a remote REST endpoint such as Azure AI Foundry or Azure OpenAI. Microsoft's CREATE EXTERNAL MODEL documentation includes a local deployment pattern using ONNX Runtime running locally with local runtime/model paths . That is the right design when embeddings must be generated inside the SQL Server instance without external network access. Microsoft explicitly documents a local ONNX Runtime example for SQL Server 2025 and notes the required local runtime setup and model path configuration.
The permission requirement is handled by granting the application user access to use the external embeddings model. Microsoft's AI_GENERATE_EMBEDDINGS documentation states that, as a prerequisite, you must create an external model of type EMBEDDINGS that is accessible via the correct grants, roles, and/or permissions . Among the choices, the exam-appropriate action is to grant execute permission on the external model project to AlApplicationUser so only that database user can run embedding generation through the model.


NEW QUESTION # 44
......

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