P.S. Free & New DP-800 dumps are available on Google Drive shared by ExamsTorrent: https://drive.google.com/open?id=1YDO_D3_uLf0LFINNECI1WPawueWBUnJB
Passing Microsoft actual test will make you stand out from other people and you will have access to the big companies. But it is not an easy thing for you to prepare DP-800 practice test. The best way for you is choosing a training tool to practice DP-800 Study Materials. If you have no idea about the training tools, ExamsTorrent will be your best partner in the way of passing the IT certification.
| Topic | Details |
|---|---|
| Topic 1 |
|
| Topic 2 |
|
| Topic 3 |
|
>> DP-800 Latest Test Simulations <<
Our ExamsTorrent can help you realize your dream to pass DP-800 certification exam by providing DP-800 test training materials. Because it concludes all training materials you need to Pass DP-800 Exam. Choosing our ExamsTorrent can absolutely help you pass DP-800 test easily, and make you become a member of elite in IT. What are you waiting for? Hurry up!
NEW QUESTION # 28
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 # 29
You need to meet the development requirements for the FeedbackJson column 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:
JSON_VALUE(f.FeedbackJson, ' $.text ' ) AS FeedbackText
CONTAINS(FeedbackJson, @Keyword)
SimilarityScore
These three selections are the correct way to complete the query because they align exactly with the stated requirements for the FeedbackJson column.
First, to extract the customer feedback text from the JSON document , the correct expression is JSON_VALUE(f.FeedbackJson, ' $.text ' ) AS FeedbackText . Microsoft documents that JSON_VALUE is used to extract a scalar value from JSON, while JSON_QUERY is used for returning an object or array .
Since $.text is the textual feedback string, JSON_VALUE is the correct function.
Second, to filter rows where the JSON text contains a keyword , the best choice is CONTAINS (FeedbackJson, @Keyword) . The scenario explicitly states that FeedbackJson already has a full-text index
, and Microsoft documents that CONTAINS is the full-text predicate used in the WHERE clause to search full-text indexed character data. That makes it more appropriate than using EDIT_DISTANCE for keyword filtering.
Third, to order the results by similarity score, highest first , the correct item is SimilarityScore in the ORDER BY clause, which would be paired with DESC in the query. This matches the requirement to sort by the computed fuzzy similarity value. The DP-800 study guide specifically includes writing queries that use fuzzy string matching functions such as EDIT_DISTANCE, which supports the earlier computed SimilarityScore expression in the query.
NEW QUESTION # 30
You need to recommend a solution that will resolve the ingestion pipeline failure issues. Which two actions should you recommend? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: C,E
Explanation:
The two correct actions are D and E because the ingestion failures are caused by malformed JSON and duplicate payloads , and these two controls address those two problems directly. Microsoft's JSON documentation states that SQL Server and Azure SQL support validating JSON with ISJSON , and Microsoft specifically recommends using a CHECK constraint to ensure JSON text stored in a column is properly formatted.
For the duplicate-payload issue, creating a unique index on a hash of the payload is the appropriate design.
Microsoft documents using hashing functions such as HASHBYTES to hash column values, and SQL Server allows a deterministic computed column to be used as a key column in a UNIQUE constraint or unique index . That makes a persisted hash-based computed column plus a unique index a practical and exam- consistent way to reject duplicate payloads efficiently.
The other options do not solve the stated root causes:
* Snapshot isolation addresses concurrency behavior, not malformed JSON or duplicate payload detection.
* A trigger to rewrite malformed JSON is not the right integrity control and is brittle.
* Foreign key constraints enforce referential integrity, not JSON validity or duplicate-payload prevention
NEW QUESTION # 31
Drag and Drop Question
You have an Azure SQL database that supports an AI-driven product search API.
You need to identify the top CPU-consuming queries from the last two hours by using Query Store data. The solution must aggregate CPU consumption across executions and return only the top 15 query hashes.
How should you complete the Transact-SQL code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 32
You are developing an Azure SQL solution by using Microsoft Visual Studio 2026. The solution uses a GitHub repository.
You plan to use GitHub Copilot Chat to access the GitHub repository tools by connecting to the GitHub MCP Server.
You need to configure Visual Studio to support the planned configuration. The solution must rely on OAuth to access the MCP server.
What should you create?
Answer: C
Explanation:
In this scenario, you need to create an mcp.json file. This file acts as the configuration bridge that tells Visual Studio 2026 and GitHub Copilot Chat how to connect to and communicate with the GitHub MCP Server.
Key Configuration Details
The mcp.json file is typically placed in your solution's root directory or a specific .mcp folder to enable project-specific tools Configuration Steps
1. Create the MCP Configuration File
You must define the connection to the GitHub MCP server so Copilot Chat can interact with your repository tools.
File Name: mcp.json
Location: Usually placed in %AppData%\Microsoft\VisualStudio\2026\mcp.json (or the project root depending on your specific extension settings).
Content:
{
"mcpServers": {
"github": {
"url": "https://api.githubcopilot.com/mcp/",
"auth": "OAuth"
}
}
}
2. Authenticate via OAuth
3. Connect Azure SQL in VS 2026
Reference:
https://www.workato.com/the-connector/mcp-server-tutorial/
NEW QUESTION # 33
......
To meet the different and specific versions of consumers, and find the greatest solution to help you review, we made three versions for you. Three versions of Developing AI-Enabled Database Solutions prepare torrents available on our test platform, including PDF version, PC version and APP online version. The trait of the software version is very practical. It can simulate real test environment, you can feel the atmosphere of the Developing AI-Enabled Database Solutions exam in advance by the software version, and install the software version several times. PDF version of DP-800 Exam torrents is convenient to read and remember, it also can be printed into papers so that you are able to write some notes or highlight the emphasis. PC version of our DP-800 test braindumps only supports windows users and it is also one of our popular types to choose.
DP-800 Reliable Exam Cram: https://www.examstorrent.com/DP-800-exam-dumps-torrent.html
BTW, DOWNLOAD part of ExamsTorrent DP-800 dumps from Cloud Storage: https://drive.google.com/open?id=1YDO_D3_uLf0LFINNECI1WPawueWBUnJB