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NEW QUESTION # 37
You have an Azure SQL database named SalesDB that supports an AI-enabled product search application.
SalesDB has a table named SalesLT.Product that contains the following columns:
ProductID (int)
Name (nvarchar(100))
ListPrice (decimal(18,2))
You need to create an object that returns products priced above a caller-provided threshold. The solution must meet the following requirements:
Support being used in a join.
Accept one input parameter.
Return a table result.
Answer:
Explanation:
Explanation:
NEW QUESTION # 38
Hotspot Question
You have an Azure SQL database that has Query Store enabled.
Query Performance Insight shows that one stored procedure has the longest runtime. The procedure runs the following parameterized query.
The dbo.Orders table has approximately 120 million rows. CustomerId is highly selective, and OrderDate is used for range filtering and sorting.
You have the following indexes:
- Clustered index: PK_Orders on (OrderId)
- Nonclustered index: IX_Orders_OrderDate on (OrderDate) with no
included columns
An actual execution plan captured from Query Store for slow runs shows the following:
- An index seek on IX_Orders_OrderDate followed by a Key Lookup
(Clustered) on PK_Orders for CustomerId, Status, and TotalAmount
- A sort operator before Top (50), because the results are ordered by
OrderDate DESC
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 39
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?
Answer: C
Explanation:
The correct answer is D because the requirement is to enable similarity search over embedding vectors and to minimize latency . Microsoft documents that CREATE VECTOR INDEX is specifically used to create an index on vector data for approximate nearest neighbor (ANN) search , which is designed to accelerate vector similarity queries compared to exact k-nearest-neighbor scans.
This matches the scenario exactly. The VehicleHealthSummary table already includes an Embeddings (vector (1536)) column. In Microsoft SQL platforms, embeddings are stored in vector columns and queried for semantic similarity. To improve performance and reduce response time, Microsoft recommends a vector index , not a regular B-tree nonclustered index and not a full-text index. A vector index is purpose-built for finding the most similar vectors efficiently.
The other options are not appropriate:
* A would require manual comparison logic and would increase latency rather than minimize it.
* B is incorrect because a standard nonclustered index is not the index type used for vector similarity operations.
* C is incorrect because full-text indexes are for textual token-based search, not numeric vector embeddings.
Microsoft's current documentation is explicit that vector indexes support approximate nearest neighbor search , and that the optimizer can use the ANN index automatically for vector queries. That is the exam- aligned design choice when the goal is fast retrieval of the most relevant health summary reports from an embeddings column.
Topic 2, Fabrikam Case
- To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Existing Environment - Azure Environment - Fabrikam has a single Azure subscription in the East US 2 Azure region. The subscription contains an Azure SQL database named DB1. DB1 contains the following tables: * Patients * Employees * Procedures * Transactions * UsefulPrompts * ProcedureDocuments You store a column master key as a secret in Azure Key Vault. You have an on-premises application named TransactionProcessing that uses a hard-coded username and password in a connection string to access DB1.
Problem Statements - Users report that after executing a long-running stored procedure named sp_UpdateProcedureForPatient, updates to the underlying data are sometimes inconsistent. Requirements - Planned Changes - Fabrikam plans to manage all changes to Azure SQL Database objects by using source control in GitHub. Every pull request submitted to production will be validated before it can be merged.
Deployments must use the Release configuration. Security Requirements - Fabrikam identifies the following security requirements: * The TransactionProcessing application must use a passwordless connection to DB1. * The Employees table contains two columns named TaxID and Salary that must be encrypted at rest. * Auditors must have a tamper-evident history of transactions with cryptographic proof of changes to the employee data. Database Performance Requirements Records accessed by using sp_UpdateProcedureForPatient must NOT be changed by other transactions while the stored procedure runs.
AI Search, Embeddings, and Vector Indexing Fabrikam identifies the following AI-related requirements: * Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF). * Users must be able to query the data in DB1 by using prompts in Copilot in Microsoft Fabric. * The UsefulPrompts table will store prompts that doctors can use to help diagnose patient illness by connecting to an Azure OpenAI endpoint.
Development Requirements - Fabrikam identifies the following development requirements: * Provide the functionality to retrieve all the transactions of a given patient between two dates, showing a running total. * Expose a Data API builder (DAB) configuration file to enable Azure services to perform the following operations over a REST API: o Read data from the procedures table without authentication. o Read and insert data into the Transactions table once authenticated. o Execute the sp_UpdateProcedurePatient stored procedure. * Provide the functionality to retrieve a list of the names of patients who underwent medical procedures during the last 30 days. * Information for each medical procedure will be stored in a table. The table will be used with a large language model (LLM) for user querying and will have the following structure.
DAB
You create a DAB configuration file that meets the development requirements for DB1 and includes the following entities.
NEW QUESTION # 40
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?
Answer: A
Explanation:
The correct answer is Option B because the requirement is to call an Azure OpenAI REST endpoint from SQL Server 2025 while providing the highest level of security , and the instance already has a managed identity enabled . For Microsoft's SQL AI features, the preferred secure pattern is to use a database scoped credential with IDENTITY = ' Managed Identity ' instead of storing an API key. Microsoft documents that SQL Server 2025 supports managed identity for external AI endpoints, and for Azure OpenAI the credential secret uses the Cognitive Services resource identifier: { " resourceid " : " https://cognitiveservices.azure.
com " } .
So line 02 should be:
WITH IDENTITY = ' Managed Identity ' ,
SECRET = ' { " resourceid " : " https://cognitiveservices.azure.com " } ' ; Why the other options are incorrect:
* A and D use HTTP header or query-string credentials with an API key , which is less secure than managed identity because a secret key must be stored and rotated manually. Microsoft recommends managed identity where supported to avoid embedded secrets.
* C mixes Managed Identity with an api-key secret, which is not the correct pattern for Azure OpenAI managed-identity authentication.
* E uses an invalid identity value for this scenario. The accepted credential identities for external REST endpoint calls include HTTPEndpointHeaders , HTTPEndpointQueryString , Managed Identity , and Shared Access Signature .
Because the endpoint is Azure OpenAI and the question explicitly asks for the highest security , managed identity with the Cognitive Services resource ID is the Microsoft-aligned answer.
NEW QUESTION # 41
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
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 references system objects.
You need to update the SQL database project to ensure that dotnet buildvalidates successfully by including the correct system objects in the database model for Azure SQL Database.
Solution: Add an artifact reference to the Azure SQL Database master.dacpac file.
Does this meet the goal?
Answer: B
Explanation:
Correct:
* Add the Microsoft.SqlServer.Dacpacs.Azure.Master NuGet package to the project.
To resolve system reference errors in an SDK-style SQL project targeting Azure SQL Database, you need to add a reference to the Microsoft.SqlServer.Dacpacs.Azure.Master NuGet package.
In your .sqlproj file, include the following item group:
<ItemGroup>
<PackageReference Include="Microsoft.SqlServer.Dacpacs.Azure.Master" Version="1.60.0" />
</ItemGroup>
Why this works:
System Objects: Standard SDK-style projects don't automatically include system views (like sys.database_principals or sys.dm_db_resource_stats). This package provides the necessary metadata for the compiler.
Azure Specifics: It includes Azure-only system objects that aren't present in the standard master database dacpac used for on-premises SQL Server.
CI/CD Friendly: Since it is a NuGet package, the dotnet build command will automatically restore it during the CI process without requiring manual file paths or local installations of Visual Studio.
Incorrect:
* Add an artifact reference to the Azure SQL Database master.dacpac file.
* Add the Microsoft.SqlServer.Dacpacs.Master NuGet package to the project.
Reference:
https://learn.microsoft.com/en-us/sql/tools/sql-database-projects/concepts/system-objects
NEW QUESTION # 42
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