DP-800試験無料問題集「Microsoft Developing AI-Enabled Database Solutions 認定」
You have an SDK-style SQL database project stored in a Git repository. The project targets an Azure SQL database.
The CI build fails with unresolved reference errors when the project ieferences system objects.
You need to update the SQL database project to ensure that dotnet build validates successfully by including the correct system objects in the database model for Azure SQL Database.
Solution: Add the Microsoft.SqlServer.Dacpacs.Mastet NuGet package to the project.
Does this meet the goal?
The CI build fails with unresolved reference errors when the project ieferences system objects.
You need to update the SQL database project to ensure that dotnet build validates successfully by including the correct system objects in the database model for Azure SQL Database.
Solution: Add the Microsoft.SqlServer.Dacpacs.Mastet NuGet package to the project.
Does this meet the goal?
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
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.
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.
正解：A,B
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解説: (GoShiken メンバーにのみ表示されます)
You have a SQL database in Microsoft Fabric that contains a column named Payload. Payload stores customer data in JSON documents that have the following format:
JSON
{
" date " : " 2026-01-25 " ,
" customer_email " : " [email protected] " ,
...
}
Data analysis shows that some customers have subaddressing in their email address; for example, [email protected].
You need to return a normalized email value that removes the subaddressing, for example, [email protected] must be normalized to [email protected].
Which Transact-SQL expression should you use?
JSON
{
" date " : " 2026-01-25 " ,
" customer_email " : " [email protected] " ,
...
}
Data analysis shows that some customers have subaddressing in their email address; for example, [email protected].
You need to return a normalized email value that removes the subaddressing, for example, [email protected] must be normalized to [email protected].
Which Transact-SQL expression should you use?
正解：A
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You have a SQL database in Microsoft Fabric that contains a column named Payload. pay load stores customer data in JSON documents that have the following format.
Data analysis shows that some customers have subaddressing in their email address, for example, [email protected].
You need to return a normalized email value that removes the subaddressing, for example, user! + [email protected] must be normalized to [email protected].
Which Transact SQL expression should you use?
Data analysis shows that some customers have subaddressing in their email address, for example, [email protected].
You need to return a normalized email value that removes the subaddressing, for example, user! + [email protected] must be normalized to [email protected].
Which Transact SQL expression should you use?
正解：D
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解説: (GoShiken メンバーにのみ表示されます)
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?
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?
正解：D
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解説: (GoShiken メンバーにのみ表示されます)
You have an Azure SQL database that contains a table named Table1. Table1 contains 25,000,000 rows of data and a datetime2 column named DateKey. The data in Table1 spans the years 2020 through 2021.
You need to partition the data in Table1 by year. The solution must minimize how long it takes to rebuild or reindex the table.
How should you complete the Transact-SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to partition the data in Table1 by year. The solution must minimize how long it takes to rebuild or reindex the table.
How should you complete the Transact-SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Partition range # RANGE RIGHT
Boundary values # ' 2020-01-01 00:00:00 ' , ' 2021-01-01 00:00:00 '
Comprehensive and Detailed Explanation with all Developing AI-Enabled Database Solutions documents: = The correct configuration is to use RANGE RIGHT with boundary values at the start of each year:
CREATE PARTITION FUNCTION PartitionByYear (datetime2)
AS RANGE RIGHT
FOR VALUES (
' 2020-01-01 00:00:00 ' ,
' 2021-01-01 00:00:00 '
);
Microsoft documents that with RANGE RIGHT, each boundary value belongs to the partition on its right. For date-based partitioning, this is the natural pattern because a boundary such as 2021-01-01 becomes the lower boundary of the 2021 partition.
With these boundaries, the resulting ranges are effectively:
Partition 1: dates before 2020-01-01
Partition 2: 2020-01-01 through before 2021-01-01
Partition 3: 2021-01-01 and later
This cleanly separates the 2020 and 2021 data into year-aligned partitions. Microsoft specifically recommends RANGE RIGHT for date-based boundaries because the first day of a period remains in the same partition as the rest of that period.
The other boundary choices are incorrect or less appropriate:
Using year-end timestamps with RANGE LEFT is more cumbersome and can be sensitive to datetime2 precision.
Monthly boundaries would partition by month, not year.
Including 2019 and a 2021-12-31 23:59:59 boundary creates unnecessary partitions and is not the cleanest year-based design.
Therefore:
First dropdown: RANGE RIGHT
Second dropdown: ' 2020-01-01 00:00:00 ' , ' 2021-01-01 00:00:00 '
You have a Microsoft SQL Server 2025 instance that has a managed identity enabled.
You have a database that contains a table named dbo.ManualChunks. dbo.ManualChunks 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 endpoint for chat completions. The solution must provide the highest level of security.
You write the following Transact-SG1 code.
What should you insert at line 02?
You have a database that contains a table named dbo.ManualChunks. dbo.ManualChunks 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 endpoint for chat completions. The solution must provide the highest level of security.
You write the following Transact-SG1 code.
What should you insert at line 02?
正解：D
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解説: (GoShiken メンバーにのみ表示されます)
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?
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?
正解：B
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You have an Azure SQL database.
You deploy Data API builder (DAB) to Azure Container Apps by using the mcr.nicrosoft.com/azure-databases
/data-api-builder:latest image.
You have the following Container Apps secrets:
* MSSQL_COMNECTiON_STRrNG that maps to the SQL connection string
* DAB_C0HFT6_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?
You deploy Data API builder (DAB) to Azure Container Apps by using the mcr.nicrosoft.com/azure-databases
/data-api-builder:latest image.
You have the following Container Apps secrets:
* MSSQL_COMNECTiON_STRrNG that maps to the SQL connection string
* DAB_C0HFT6_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?
正解：B
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解説: (GoShiken メンバーにのみ表示されます)
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.
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.
正解：
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.