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Microsoft DP-800 Exam Syllabus Topics:

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

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Microsoft Developing AI-Enabled Database Solutions Sample Questions (Q21-Q26):

NEW QUESTION # 21
What is the role of Azure Synapse in AI + SQL solutions?

Answer: D

Explanation:
Azure Synapse Analytics combines big data and data warehousing for AI-driven insights.


NEW QUESTION # 22
You need to recommend a solution for the development team to retrieve the live metadata. The solution must meet the development requirements.
What should you include in the recommendation?

Answer: B


NEW QUESTION # 23
You have an Azure SQL database.
You deploy Data API builder (DAB) to Azure Container Apps by using the
mcr.microsoft.com/azure-databases/data-api-builder:latest image.
You have the following Container Apps secrets:
- MSSQL_CONNECTION_STRING that maps to the SQL connection string
- DAB_CONFIG_BASE64 that maps to the DAB configuration
You need to initialize the DAB configuration to read the SQL connection string.
Which command should you run?

Answer: D

Explanation:
To initialize the Data API builder (DAB) configuration to read the SQL connection string from your Container Apps secret, use the following dab init command:
dab init --database-type mssql --connection-string "@env('MSSQL_CONNECTION_STRING')" Why this command works
--database-type mssql: Specifies that you are connecting to an Azure SQL or SQL Server database.
@env('MSSQL_CONNECTION_STRING'): This is the built-in DAB function that tells the runtime to substitute the value of the specified environment variable at load time. Since your Container Apps secret is mapped to MSSQL_CONNECTION_STRING, DAB will resolve it automatically when the container starts.
--connection-string: This flag sets the data source connection. By using the @env() syntax here, you ensure the secret remains out of the static configuration file.
Reference:
https://learn.microsoft.com/en-us/azure/data-api-builder/command-line/dab-init


NEW QUESTION # 24
You have a database that contains production data. The schema is stored in a Git repository as an SDK-style SQL database project and contains the following reference data.
Name
Data type
RefID
int, identity
Code
nvarchar(10)
CreatedDate
datetime2
Description
nvarchar(255)
A deployment pipeline can be rerun automatically when a transient failure occurs.
You need to deploy the reference data as part of the same CI/CD process. Rerunning the pipeline must produce the same outcome and must NOT create duplicate rows.
What should you do?

Answer: A


NEW QUESTION # 25
You have an Azure SQL database that contains a table named dbo.ManualChunks. dbo.HonualChunks contains product manuals A retrieval query already returns the top five matching chunks as nvarchar(max) text.
You need to call an Azure OpenAI REST endpomt for chat completions. The request body must include both the user question and theretiieved chunks.
You write the following Transact-SQL code.

What should you insert at line 22?

Answer: D

Explanation:
The correct insertion at line 22 is FOR JSON PATH, WITHOUT_ARRAY_WRAPPER .
The request body for the Azure OpenAI chat completions call must be a single JSON object containing the messages array with both the system/user content and the retrieved chunks. Microsoft documents that FOR JSON PATH is the preferred way to shape JSON output, especially when you want precise control over nested property names like messages[0].role and messages[1] .content.
The key detail is WITHOUT_ARRAY_WRAPPER . By default, FOR JSON returns results enclosed in square brackets as a JSON array. Microsoft documents that WITHOUT_ARRAY_WRAPPER removes those brackets so a single JSON object is produced instead. That is exactly what is needed here for @payload, because the stored procedure is building one request body, not an array of request bodies.


NEW QUESTION # 26
......

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