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Microsoft Developing AI-Enabled Database Solutions : DP-800

DP-800

Exam Code: DP-800

Exam Name: Developing AI-Enabled Database Solutions

Updated: Oct 31, 2026

Q & A: 101 Questions and Answers

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About Microsoft Developing AI-Enabled Database Solutions certification

Microsoft DP-800 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Design and develop database solutions: This domain covers designing and building database objects such as tables, views, functions, stored procedures, and triggers, along with writing advanced T-SQL code and leveraging AI-assisted tools like GitHub Copilot and MCP for SQL development.
Topic 2
  • Implement AI capabilities in database solutions: This domain covers designing and managing external AI models and embeddings, implementing full-text, semantic vector, and hybrid search strategies, and building retrieval-augmented generation (RAG) solutions that connect database outputs with language models.
Topic 3
  • Secure, optimize, and deploy database solutions: This domain focuses on implementing data security measures like encryption, masking, and row-level security, optimizing query performance, managing CI
  • CD pipelines using SQL Database Projects, and integrating SQL solutions with Azure services including Data API builder and monitoring tools.

Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-800

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Microsoft Developing AI-Enabled Database Solutions Sample Questions:

Question #1
You have a GitHub Actions workflow that builds and deploys an Azure SQL database. The schema is stored in a GitHub repository as an SDK-style SQL database project.
Following a code review, you discover that you need to generate a report that shows whether the production schema has diverged from the model in source control.
Which action should you add to the pipeline?

A. SqlPackage.exe /Action:Script
B. SqlPackage.exe /Action:DeployReport
C. SqlPackage.exe /Action:DriftReport
D. SqlPackage.exe /Action:Extract


Question #2
You have an Azure SQL database named ToDo that contains a table named dbo.ToDo.
Your company plans to develop an Azure Functions app to run whenever the rows in dbo.ToDo change. The app will process INSERT, UPDATE, and DELETE events by using the Azure SQL trigger binding.
You need to configure ToDo to support the planned app.
What should you do?

A. Enable change data capture (CDC) on ToDo and dbo.ToDo.
B. On dbo.ToDo, create a Data Definition Language (DDL) trigger that calls the Azure Functions HTTP endpoint.
C. On dbo.ToDo, create a Data Manipulation Language (DML) trigger that calls the Azure Functions HTTP endpoint.
D. Enable change tracking on ToDo and dbo.ToDo.


Question #3
You have an Azure SQL database that supports the OLTP workload of an order-processing application.
During a 10-minute incident window, you run a dynamic management view query and discover the following:
Session 72 is sleeping with open_transaction_count = 1.
Multiple other sessions show blocking_session_id = 72 in sys.dm_exec_requests.
sys.dm_exec_input_buffer(72, NULL) returns only BEGIN TRANSACTION UPDATE Sales.Orders.
Users report that updates to Sales.Orders intermittently time out during the incident window. The timeouts stop only after you manually terminate session 72.
What is a possible cause of the blocking?

A. An explicit transaction was started but not committed or rolled back.
B. A long-running SELECT statement is blocking writers.
C. Session 72 caused a deadlock.
D. A lock escalation occurred.


Question #4
You have an Azure SQL database that supports a customer-facing API. The API calls a stored procedure named dbo.GetCustomerOrders thousands of times per hour.
After a deployment that updated indexes and statistics, users report that the API endpoint backed by dbo.
Getcustomerorders is slower. In Query Store, the same query now has two persisted execution plans. During the last hour, the newer plan had a significantly higher average duration and CPU time than the older plan.
You need to restore the previous performance quickly, without changing the API code.
Which Transact-SQL command should you run?

A. ALTER DATABASE
B. DBCC FREEPROCCACHE
C. EXEC sp_query_store_force_plan
D. EXEC sys.sp_query_store_set_hints


Question #5
You have an Azure SQL database that contains tables named dbo.ProduetDocs and dbo.
ProductuocsEnbeddings. dbo.ProductOocs contains product documentation and the following columns:
* Docld (int)
* Title (nvdrchdr(200))
* Body (nvarthar(max))
* LastHodified (datetime2)
The documentation is edited throughout the day. dbo.ProductDocsEabeddings contains the following columns:
* Dotid (int)
* ChunkOrder (int)
* ChunkText (nvarchar(aax))
* Embedding (vector(1536))
The current embedding pipeline runs once per night
Vou need to ensure that embeddings are updated every time the underlying documentation content changes The solution must NOT ' equire a nightly batch process.
What should you include in the solution?

A. fixed-size chunking
B. a smaller embedding model
C. change tracking on dbo.ProductDocs
D. table triggers


Solutions:

Question #1
Correct Answer: C
Question #2
Correct Answer: C
Question #3
Correct Answer: A
Question #4
Correct Answer: C
Question #5
Correct Answer: C

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