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Microsoft DP-800 Exam Syllabus Topics:

Section	Weight	Objectives
Implement AI capabilities in database solutions	25-30%	- Build intelligent search and retrieval 1. Implement semantic search and RAG patterns 2. Design and implement embedding pipelines 3. Optimize search performance and relevance - 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
Secure, optimize, and deploy database solutions	35-40%	- Deploy and maintain solutions 1. Manage updates and versioning 2. Deploy across SQL Server, Azure SQL, and Microsoft Fabric 3. Implement CI/CD for databases - Secure database solutions 1. Protect data at rest and in transit 2. Implement authentication and authorization 3. Implement compliance and auditing - Optimize performance and reliability 1. Monitor and troubleshoot performance 2. Ensure high availability and disaster recovery 3. Optimize queries and indexes
Design and develop database solutions	35-40%	- Develop database solutions 1. Implement data integration and transformation 2. Write and optimize T-SQL code 3. Implement database objects and structures - 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

Section

Weight

Objectives

Implement AI capabilities in database solutions

25-30%

- Build intelligent search and retrieval

1. Implement semantic search and RAG patterns
2. Design and implement embedding pipelines
3. Optimize search performance and relevance

- 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

Secure, optimize, and deploy database solutions

35-40%

- Deploy and maintain solutions

1. Manage updates and versioning
2. Deploy across SQL Server, Azure SQL, and Microsoft Fabric
3. Implement CI/CD for databases

- Secure database solutions

1. Protect data at rest and in transit
2. Implement authentication and authorization
3. Implement compliance and auditing

- Optimize performance and reliability

1. Monitor and troubleshoot performance
2. Ensure high availability and disaster recovery
3. Optimize queries and indexes

Design and develop database solutions

35-40%

- Develop database solutions

1. Implement data integration and transformation
2. Write and optimize T-SQL code
3. Implement database objects and structures

- 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

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Microsoft Developing AI-Enabled Database Solutions DP-800 Prüfungsfragen mit Lösungen (Q58-Q63):

58. Frage
You have an Azure SQL database named AdventureWorksDB that contains a table named dbo.Employee.
You have a C# Azure Functions app that uses an HTTP-triggered function with an Azure SQL input binding to query dbo.Employee.
You are adding a second function that will react to row changes in dbo.Employee and write structured logs.
You need to configure AdventureWorksDB and the app to meet the following requirements:
* Changes to dbo.Employee must trigger the new function within five seconds.
* Each invocation must processes no more than 100 changes.
Which two database configurations should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Create an AFTER trigger on dbo.Employee for Data Manipulation Language (DML).
B. Enable change tracking at the database level.
C. Enable change data capture (CDC) for dbo.Employee table changes
D. Enable change tracking on the dbo. Employee table.
E. SetSql Trigger MaxBatchSize to 100.
F. Set Sql_Trigger_PollingIntervalMs to 5000.

Antwort: D,F

59. Frage
You need to enable similarity search to provide the analysts with the ability to retrieve the most relevant health summary reports. The solution must minimize latency.
What should you include in the solution?

A. a standard nonclustered index on the Fmbeddings (vector (1536)) column
B. a full-text index on the Fmbeddings (vector (1536)) column
C. a vector index on the Embedding* (vector (1536)) column
D. a computed column that manually compares vector values

Antwort: C

60. Frage
You have an Azure SQL database named ProductsDB.
You deploy Data API builder (DAB) to Azure Container Apps by using the [mcr.microsoft.com/azure- databases/data-api-builder:latest](https://mcr.microsoft.com/azure-databases/data-api-builder:latest) image.
The container app has the following configurations:
Secrets: mssql-connection-string, dab-config-base64
Environment variables:
MSSQL_CONNECTION_STRING=secretref:mssql-connection-string
DAB_CONFIG_BASE64=secretref:dab-config-base64
Ingress: External on port 5000
Users report that the /health endpoint returns a healthy response, but all requests that query an entity named Products fail and generate a connection error.
You confirm that the SQL login in the connection string is correct and the database exists.
You need to ensure that the container app can establish connections to the Azure SQL logical server without changing the container app deployment settings or the DAB configuration file.
What should you do on the Azure SQL logical server?

A. Create a firewall rule that allows a start and end IP address of 0.0.0.0.
B. Create an auto-failover group for ProductsDB.
C. Run DBCC CHECKDB on ProductsDB.
D. Enable FORCE_LAST_GOOD_PLAN automatic tuning for ProductsDB.

Antwort: A

61. Frage
Drag and Drop Question
You have an Azure SQL database named DB1 that contains two tables named knowledge_base and query_cache. knowledge_base contains support articles and embeddings. query_cache contains chat questions, responses, and embeddings. DB1 supports an AI-enabled chat agent.
You need to design a solution that meets the following requirements:
- Serializes the retrieved rows from knowledge_base
- Extracts the answer field from the response
- Extracts the embeddings to store in query_cache
You will call the external large language model (LLM) by using the
sp_invoke_external_rest_endpoint stored procedure.
Which Transact-SQL commands should you use for each requirement? To answer, drag the appropriate commands to the correct requirements. 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.

Antwort:

Begründung:

62. Frage
You create an SDK-style SQL database project in Microsoft Visual Studio Code named Database.sqlproj and add the project to a GitHub repository.
You need to configure a GitHub Actions workflow to support the planned changes for DB1.
How should you complete the workflow? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Antwort:

Begründung:

Explanation:
* pull_request
* build Database.sqlproj -c Release
The correct configuration is pull_request with dotnet build Database.sqlproj -c Release.
Fabrikam requires every pull request targeting production to be validated before merging, and all deployments must use the Release configuration.
Technical breakdown:
1. pull_request trigger: Executes the GitHub Actions workflow when a pull request targets the main branch.
This allows SQL project validation before changes are merged.
2. dotnet build: Compiles the SDK-style SQL database project, validates its database schema model, and produces a .dacpac deployment artifact.
3. -c Release: Explicitly selects the Release build configuration, satisfying Fabrikam ' s deployment configuration requirement.
4. Branch protection: Configure GitHub branch protection rules to make successful validation a required status check before merging. The workflow alone does not enforce this restriction.
5. Incorrect alternatives: push runs after changes are pushed, while merge is not a valid GitHub Actions event.
dotnet pack packages projects, and dotnet publish is not the appropriate SQL project validation command.
Microsoft identifies dotnet build as the supported compilation method for SDK-style SQL projects.
Completed GitHub Actions workflow
name: Validate SQL Project
on:
pull_request:
branches: [ " main " ]
jobs:
validate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Step 1
run: dotnet build Database.sqlproj -c Release
DP-800 Official Study Guide Reference:
Main topic: Secure, optimize, and deploy database solutions.
Subtopic: Implement CI/CD by using SQL Database Projects.
Specific examination objectives:
* Create, build, and validate database models by using SQL Database Projects, including SDK-style models.
* Manage branching, pull requests, and conflict resolution.
* Design and implement controls for deployment pipelines.

63. Frage
......

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