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| Section | Weight | Objectives |
|---|---|---|
| Design and develop database solutions (35โ40%) | 35-40% | - Design and implement programmability objects
|
| Secure, optimize, and deploy database solutions (35โ40%) | 35-40% | - Implement data platform resources
|
| Implement AI capabilities in database solutions (25โ30%) | 25-30% | - Implement AI features
|
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NEW QUESTION # 59
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 HATCH 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?
Answer: A
Explanation:
The correct query is Option D because it starts from the input person and uses exactly two directed Knows edges in a single MATCH pattern:
MATCH(p1-(k1)- > p2-(k2)- > p3)
Microsoft documents that SQL Graph uses the MATCH predicate in the WHERE clause to express graph traversal patterns over node and edge tables, and directed relationships are written with arrow syntax such as node1-(edge)- > node2.
Why D is correct:
* It anchors the starting node with p1.PersonId = @StartPersonId.
* It traverses two directed hops : p1 - > p2 - > p3.
* It returns p3.PersonId, p3.DisplayName, which are the people reachable in exactly two Knows relationships.
Why the others are wrong:
* A filters on DisplayName = DisplayName, which is unrelated to the required input parameter and does not correctly anchor the start node.
* B reverses the traversal direction in the pattern.
* C uses two separate MATCH predicates instead of the required single two-hop directed pattern. The proper graph pattern syntax supports chaining the hops directly in one MATCH expression.
Topic 1, Contoso Case Study
Existing Environment
Contoso has an Azure subscription in North Europe that contains the corporate infrastructure. The current infrastructure contains a Microsoft SQL Server 2017 database. The database contains the following tables.
The FeedbackJson column has a full-text index and stores JSON documents in the following format.
The support staff at Contoso never has the unmask permission.
Requirements
Contoso is deploying a new Azure SQL database that will become the authoritative data store for the following;
* Al workloads
* Vector search
* Modernized API access
* Retrieval Augmented Generation (RAG) pipelines
Sometimes the ingestion pipeline fails due to malformed JSON and duplicate payloads.
The engineers at Contoso report that the following dashboard query runs slowly.
SELECT VehicleTd, Lastupdatedutc, EngineStatus, BatteryHealth FROM dbo.VehicleHealthSumary where fleetld - gFleetld ORDER BV LastUpdatedUtc DESC; You review the execution plan and discover that the plan shows a clustered index scan.
vehicleincidentReports often contains details about the weather, traffic conditions, and location. Analysts report that it is difficult to find similar incidents based on these details.
Planned Changes
Contoso wants to modernize Fleet Intelligence Platform to support Al-powered semantic search over incident reports.
Security Requirements
Contoso identifies the following telemetry requirements:
* Telemetry data must be stored in a partitioned table.
* Telemetry data must provide predictable performance for ingestion and retention operations.
* latitude, longitude, and accuracy JSON properties must be filtered by using an index seek.
Contoso identifies the following maintenance data requirements:
* Ensure that any changes to a row in the MaintenanceEvents table updates the corresponding value in the LastModif reduce column to the time of the change.
* Avoid recursive updates.
AI Search, Embedding's, and Vector indexing
The development learn at Contoso will use Microsoft Visual Studio Code and GitHub Copilot and will retrieve live metadata from the databases. Contoso identifies the following requirements for querying data in the FeedbackJson column of the customer-Feedback table:
* Extract the customer feedback text from the JSON document.
* Filter rows where the JSON text contains a keyword.
* Calculate a fuzzy similarity score between the feedback text and a known issue description.
* Order the results by similarity score, with the highest score first.
NEW QUESTION # 60
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 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?
Answer: B
Explanation:
Even if the login credentials are correct, Azure SQL Database blocks all incoming traffic by default. Since your Container App is returning a healthy response for the /health endpoint (which is internal to the DAB engine) but failing on entity queries (which require a database hit), the network handshake is being rejected at the SQL Server firewall level.
To fix this connection error without changing the container app or the DAB configuration file, you must enable the Azure SQL Server firewall to allow Azure services.
Setting the start and end IP address to 0.0.0.0 in an Azure SQL Database firewall rule is a specific configuration that enables the "Allow Azure services and resources to access this server" setting.
Primary Use Case
In your scenario, this rule allows your Azure Container Apps (ACA) to communicate with your Azure SQL Database over the Azure backbone network.
Connectivity: It permits any traffic originating from within the Azure boundary to reach the database.
Simplicity: You do not need to track or white-list the specific outbound IP addresses of your Container App, which can change if the app scales or restarts.
Internal Routing: Traffic stays within the Azure network rather than routing out to the public internet and back in.
Reference:
https://learn.microsoft.com/en-us/azure/azure-sql/database/firewall-configure
https://stackoverflow.com/questions/54599813/how-to-enable-the-access-to-azure-services-in- my-azure-sql-database-server
NEW QUESTION # 61
You have a Microsoft SQL Servei 2025 database that contains a table named dbo.Customer-Messages, dbo.
Customer-Messages contains two columns named HessagelD (int) and MessageRaw (nvarchar(iux)).
MessageRaw can contain a phone number in multiple formats. and some rows do NOT contain a phone number. You need to write a single SELECT query that meets the following requirements:
* The query must return Message ID, RawNumber. DigitsOnly, and PhoneStatus.
* RawNumber must contain the first substring that matches a phone-number pattern, or NULL if no match exists.
* DigitsOnly must remove all non-digit characters from RawNumber. or return NULL.
* PhoneStatus must return Valid when a phone number exists in MessageRaw. otherwise return Missing.
How should you complete the Transact-SQL query? lo 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.
Answer:
Explanation:
Explanation:
The correct drag-and-drop mapping is based on the documented behavior of the new SQL regular expression functions.
For RawNumber , the requirement is to return the first substring in MessageRaw that matches the phone- number pattern, or NULL if nothing matches. That is exactly what REGEXP_SUBSTR does: it extracts the matched substring from the source text. Microsoft documents REGEXP_SUBSTR as the function that
"extracts parts of a string based on a regular expression pattern" and returns the matched occurrence.
For DigitsOnly , you first need the matched phone substring, then remove all non-digit characters from it. The correct combined expression is REGEXP_REPLACE( REGEXP_SUBSTR( so the matched substring is passed into REGEXP_REPLACE, which strips characters matching \D. Microsoft documents REGEXP_REPLACE as returning a modified source string with matching patterns replaced. Using it around REGEXP_SUBSTR satisfies the "digits only or NULL" requirement in one select expression.
For PhoneStatus , the requirement is simply to return Valid when a phone number exists and Missing otherwise. That is a Boolean test, so REGEXP_LIKE is the right function. Microsoft documents REGEXP_LIKE as returning a Boolean value indicating whether the input matches the regex pattern.
NEW QUESTION # 62
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 build validates successfully by including the correct system objects in the database model for Azure SQL Database.
Solution: Add the Microsoft.SqlServer.Dacpacs.Master NuGet package to the project.
Does this meet the goal?
Answer: A
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 # 63
You have a SQL database in Microsoft Fabric named SalesDB that contains a table named dbo.Products.
You need to modify SalesDB 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.
Answer:
Explanation:
Explanation:
Verified Answer : =
* Vector index column # embedding
* Vector search function # VECTOR_SEARCH
* Final clause # ORDER BY s.distance
The first selection is embedding because CREATE VECTOR INDEX must target the column that stores vector data. Microsoft documents the syntax as CREATE VECTOR INDEX ... ON object (vector_column) , so the index belongs on dbo.Products.embedding , not on distance or product_name .
The second selection is VECTOR_SEARCH . This function is designed for vector similarity retrieval and works with vector indexes in SQL database in Microsoft Fabric . In the shown code, the supplied
@query_vector VECTOR(1536) is compared against the embedding column using cosine distance, and TOP_N = 10 requests the ten nearest matches. Microsoft specifically documents VECTOR_SEARCH for approximate nearest-neighbor searches and its integration with vector indexes.
The final clause is ORDER BY s.distance because VECTOR_SEARCH returns a distance value representing how far each stored vector is from the supplied query vector. With cosine distance, smaller distance means greater similarity , so ascending order returns the most relevant products first.
Therefore, the completed selections are:
CREATE VECTOR INDEX idx_products_embedding
ON dbo.Products (embedding)
WITH (METRIC = ' cosine ' , TYPE = ' DiskANN ' );
FROM VECTOR_SEARCH (
TABLE = dbo.Products AS t,
COLUMN = embedding,
SIMILAR_TO = @query_vector,
METRIC = ' cosine ' ,
TOP_N = 10
) AS s
ORDER BY s.distance;
So the verified hotspot answers are embedding # VECTOR_SEARCH # ORDER BY s.distance .
NEW QUESTION # 64
......
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