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70. Frage
You have a SQL database in Microsoft Fabric named Sales BD that contains a table named dbo.Products. You need to modify SalesBD to meet the following requirements:
* Create a vector index on the appropriate column.
* Use a supplied natural language query vector.
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.
Antwort:
Begründung:
Explanation:
The first correct selection is embedding because a vector index must be created on the vector column , not on a scalar distance column or a text column such as product_name. Microsoft's CREATE VECTOR INDEX documentation shows that the index is created directly on the vector-valued column, for example ON product_embeddings(embedding).
The second correct selection is VECTOR_SEARCH because the requirement is to use a supplied natural language query vector and search against the indexed embeddings. Microsoft documents that VECTOR_SEARCH is the Transact-SQL function for approximate nearest neighbor vector retrieval and that it applies to SQL database in Microsoft Fabric as well as other supported SQL platforms.
This also matches the shown code pattern:
* declare a vector variable such as @query_vector VECTOR(1536),
* create a vector index on dbo.Products(embedding),
* query with VECTOR_SEARCH(... SIMILAR_TO = @query_vector, METRIC = ' cosine ' , TOP_N =
10).
71. Frage
Drag and Drop Question
You have an Azure SQL database that contains a table named dbo.Customers. dbo.Customers contains the following columns:
- CustomerId (int)(primary key)
- ProfileJson (nvarchar(max))
You have an application that returns phone numbers in a format of +000 000-000-0000. The phone numbers are stored in ProfileJson.
You need to write a query that returns:
- One row per customer
- A PhoneNUmerals column that contains only the digits
How should you complete the Transact-SQL query? To answer, drag the appropriate values to the correct targets. Each value 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:
72. Frage
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?
Antwort: D
Begründung:
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.
73. Frage
You have an Azure SQL database That contains a table named dbo.Products, dbo.Products contains three columns named Embedding Category, and Price. The Embedding column is defined as VECTOR(1536).
You use Ai_GENERME_EMBEDOINGS and VECTOR_SEARCH to support semantic search and apply additional filters on two columns named Category and Price.
You plan to change the embedding model from text-embedding-ada-002 to text-embedding-3-smalL Existing rows already contain embeddings in the Embedding column.
You need to implement the model change. Applications must be able to use VECTOR_SEARCH without runtime errors.
What should you do first?
Antwort: A
74. Frage
You have an Azure SQL database that contains the following SQL graph tables:
- A NODE table named dbo.Person
- An EDGE table named dbo.Knows
Each row in dbo.Person contains the following columns:
- PersonID (int)
- DisplayName (nvarchar(100))
You need to use a MATCH operator and exactly two directed Knows relationships to return the PersonID and DisplayName of people that are reachable from the person identified by an input parameter named @StartPersonId.
Which Transact-SQL query should you use?
Antwort: B
Begründung:
To achieve this using SQL Graph in Azure SQL, you use the MATCH clause to define the path.
Since you need exactly two directed relationships (A → B → C), you must chain the edge table twice in the same direction.
Transact-SQL Statement
SELECT
Person3.ID,
Person3.NameColumn -- Replace with your actual nvarchar(100) column name FROM PersonNodeTable AS Person1, KnowsEdgeTable AS Knows1, PersonNodeTable AS Person2, KnowsEdgeTable AS Knows2, PersonNodeTable AS Person3 WHERE MATCH(Person1-(Knows1)->Person2-(Knows2)->Person3) AND Person1.ID = @InputID; Use code with caution.
Key Components
MATCH Clause: Defines the traversal pattern. The syntax (Node)-(Edge)->(Node) ensures the relationship is directed.
Chaining: To get "exactly two" steps, you define three node aliases and two edge aliases.
Aliases: Each instance of the table must have a unique alias (e.g., Person1, Person2, Person3) so the engine can distinguish between the different points in the path.
Filtering: The WHERE clause uses your input parameter (@InputID) to set the starting point of the graph traversal Incorrect:
[Not A]
Need three persons, not two.
[Not B]
Do not use JOIN.
[Not C]
Incorrect MATCH statement.
Reference:
https://learn.microsoft.com/en-us/sql/relational-databases/graphs/sql-graph-sample
75. Frage
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