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| Section | Objectives |
|---|---|
| Topic 1: Develop and manage database solutions | - Optimize performance and scalability - Ensure security and compliance of data solutions |
| Topic 2: Monitor, troubleshoot, and maintain solutions | - Monitoring database health and performance - Troubleshooting data pipeline issues |
| Topic 3: Integrate AI capabilities with database systems | - Implement AI-assisted data processing - Use Azure AI services with database workloads |
| Topic 4: Design and implement data solutions | - Implement data storage and data processing solutions - Design database solutions using Azure data services |
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NEW QUESTION # 68
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 # 69
You are developing an Azure SQL database solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
You need to ensure that GitHub Copilot Chat can call the hosted GitHub MCP Server tools by using OAuth.
The MCP server configuration must be scoped to the repository.
What should you do in Visual Studio Code?
Answer: A
NEW QUESTION # 70
You have an Azure SQL database that contains a table named dbo.SupportTickets. dbo.SupportTickets contains a JSON column named Payload and a datetime column CreatedAt.
You need to generate a report for the last seven days that meets the following requirements:
* Returns exactly one row per customer per day
* For each customer and day, returns the earliest ticket
* Includes the customer ID stored in Payload
How should you complete the Transact-SQL query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
CustomerId extraction # JSON_VALUE
Ranking function # ROW_NUMBER
Final filter # 1
The first selection is JSON_VALUE because CustomerId is stored as a scalar property in the JSON payload at
$.customer.id. Microsoft documents that JSON_VALUE extracts a scalar value from JSON text, whereas OPENJSON is used to shred JSON into relational rows/columns.
The second selection is ROW_NUMBER. The query partitions the data by:
CAST(t.CreatedAt AS date),
JSON_VALUE(t.Payload, ' $.customer.id ' )
and orders each partition by:
t.CreatedAt ASC
Microsoft documents that ROW_NUMBER() assigns sequential numbers starting at 1 within each partition.
Therefore, the earliest ticket for each customer on each day receives rn = 1.
The third selection is therefore 1, because filtering with:
WHERE rn = 1
returns exactly one row per customer per calendar day-the earliest ticket in that partition.
So the completed logic is:
WITH TicketRanks AS
(
SELECT
t.TicketId,
CAST(t.CreatedAt AS date) AS TicketDate,
JSON_VALUE(t.Payload, ' $.customer.id ' ) AS CustomerId,
t.CreatedAt,
ROW_NUMBER() OVER
(
PARTITION BY
CAST(t.CreatedAt AS date),
JSON_VALUE(t.Payload, ' $.customer.id ' )
ORDER BY t.CreatedAt ASC
) AS rn
FROM dbo.SupportTickets AS t
WHERE t.CreatedAt > = DATEADD(day, -7, SYSUTCDATETIME())
)
SELECT
TicketDate,
CustomerId,
TicketId,
CreatedAt
FROM TicketRanks
WHERE rn = 1
ORDER BY TicketDate, CustomerId;
Final hotspot selections:
First dropdown: JSON_VALUE
Second dropdown: ROW_NUMBER
Third dropdown: 1
NEW QUESTION # 71
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 a SQL database in Microsoft Fabric that contains a table named dbo.Orders.
dbo.Orders has a clustered index, contains three years of data, and is partitioned by a column named OrderDate by month.
You need to remove all the rows for the oldest month. The solution must minimize the impact on other queries that access the data in dbo.Orders.
Solution: Run the following Transact-SQL statement.
TRUNCATE TABLE dbo.Orders;
Does this meet the goal?
Answer: A
Explanation:
Correct:
* Identify the partition number for the oldest month, and then run the following Transact-SQL statement.
TRUNCATE TABLE dbo.Orders
WITH (PARTITIONS (partition number));
The best Transact-SQL statement to remove all rows for the oldest month while minimizing the impact on other queries is TRUNCATE TABLE with a WITH (PARTITIONS (...)) clause.
Why TRUNCATE TABLE ... WITH (PARTITIONS (...)) is Best
Efficiency: TRUNCATE TABLE is a Data Definition Language (DDL) operation that removes data by deallocating the data pages, which is a metadata operation and is very fast, regardless of the amount of data in the partition.
Minimal Logging: It uses less transaction log space compared to a DELETE statement, which logs each row deletion individually.
Low Impact on Concurrency: It performs a quick, partition-specific operation. A row-by-row DELETE would be a long-running transaction and could cause locking and blocking issues for other queries accessing the table.
Data Integrity: Because the table has a clustered index and is partitioned by the same column (aligned indexes), the TRUNCATE PARTITION operation is a fast, partition-level maintenance operation that targets only that specific data subset.
Incorrect:
* : Identify the partition scheme for the oldest month, and then run the following Transact-SQL statement.
ALTER TABLE dbo.Orders
DROP PARTITION SCHEME (partition_scheme_name);
The DROP PARTITION SCHEME statement removes the partition scheme object from the database but does not remove the data itself or free up the space, and it requires all tables to be moved off the scheme first, which is a complex operation. This does not meet the goal of removing the data efficiently.
* Run the following Transact-SQL statement.
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());
A standard DELETE statement, even with a WHERE clause that uses the partition column, can be a time-consuming, logged operation that causes locking and blocking on the main table, negatively impacting performance.
* Run the following Transact-SQL statement.
TRUNCATE TABLE dbo.Orders;
Reference:
https://stackoverflow.com/questions/63632963/truncate-partition-vs-drop-partition-performace- wise-which-one-is-efficient-an
NEW QUESTION # 72
You are developing an Azure SQL database solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
You need to ensure that GitHub Copilot Chat can call the hosted GitHub MCP Server tools by using OAuth. The MCP server configuration must be scoped to the repository.
What should you do in Visual Studio Code?
Answer: C
Explanation:
To connect GitHub Copilot Chat to an Azure SQL Database using a hosted GitHub MCP (Model Context Protocol) Server, follow these steps. This setup ensures that Copilot can interact directly with your repository and database schema using OAuth.
Step 1: Configure the MCP Server in VS Code
You must set the scope to the Workspace level to ensure the server is restricted to your specific repository.
Open your locally cloned GitHub repository in VS Code.
Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P).
Type and select: MCP: Add Server.
Select HTTP (HTTP or Server-Sent Events).
Enter the URL: https://api.githubcopilot.com/mcp/
Crucial: When prompted for the configuration scope, select Workspace Settings.
This saves the config to .vscode/settings.json, binding the server to this repo.
Step 2: Authenticate via OAuth
Once the server is added, Copilot needs permission to act on your behalf.
Open the GitHub Copilot Chat panel.
You will see a notification or a prompt within the chat asking to Authorize the MCP server.
Follow the browser prompts to sign in and grant OAuth permissions.
This allows the hosted MCP server to "see" your repository's code and metadata.
Reference:
https://skywork.ai/skypage/en/The-Ultimate-Guide-to-GitHub's-MCP-Server:-Bridging-AI-and- Your-Codebase/1970685991323758592
NEW QUESTION # 73
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