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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Exam Format: | Case studies, Multiple select, Build list, Multiple choice, Drag and drop |
| Exam Price: | $165 USD |
| Certificate Validity Period: | 1 year |
| Available Languages: | German, Chinese (Simplified), Arabic (Saudi Arabia), Chinese (Traditional), English, Japanese, Indonesian (Indonesia), Portuguese (Brazil), Korean, Italian, French, Spanish |
| Passing Score: | 700 |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 100 minutes |
| Related Certifications: | Microsoft Certified: SQL AI Developer Associate |
| Sample Questions: | Microsoft DP-800 Sample Questions |
| Exam Way: | Online proctored or in-person at a testing center |
| Pre Condition: | No specific prerequisites, but candidates should have experience with SQL and a basic understanding of Azure services. Familiarity with AI or machine learning concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-800/ |
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NEW QUESTION # 59
Which data type is used to store vector embeddings in SQL?
Answer: B
Explanation:
Embeddings are stored as arrays or binary/vector types depending on SQL engine support.
NEW QUESTION # 60
What is Retrieval-Augmented Generation (RAG)?
Answer: D
Explanation:
RAG enhances LLM responses by retrieving relevant SQL data before generating answers.
NEW QUESTION # 61
You have a SQL database in Microsoft Fabric that contains a nvarchar (max) column named MessageText. An ID is always contained within the first paragraph of MessageText.
You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText.
What should you include in the query?
Answer: C
Explanation:
To extract an ID (e.g., alphanumeric) from the first paragraph of an nvarchar(max) column in Microsoft Fabric using STRING_ESCAPE, use STRING_SPLIT or CHARINDEX to isolate the first paragraph, apply STRING_ESCAPE, and a regex pattern.
Note: T-SQL does not natively support a REGEXP_SUBSTR function like Oracle/Snowflake. The solution below uses STRING_ESCAPE followed by pattern matching via PATINDEX and SUBSTRING to extract a typical alphanumeric ID.
Reference:
https://learn.microsoft.com/en-us/sql/t-sql/queries/contains-transact-sql
NEW QUESTION # 62
You have an Azure SQL database named DB1 that contains two tables named knowledgebase and query_cache. knowledge_base contains support articles and embeddings. query_cache contains chat questions, responses, and embeddings DB1 supports an Al-enabled chat agent.
You need to design a solution that meets the following requirements:
* Serializes the retrieved rows from knowledee_base
* Extracts the answer field from the response
* Extracts the embeddings to store in query_cache
You will call the external large language model (LLM) by using the sp_irwoke_external_re standpoint stored procedure.
Which Transact-SGL commands should you use for each requirement? To answer, drag the appropriate commands to the correct requirements. Each command may be used once, mote 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 mapping is:
* FOR JSON PATH
* JSON_VALUE
* JSON_QUERY
To serialize the retrieved rows from knowledge_base , the correct command is FOR JSON PATH .
Microsoft documents that FOR JSON formats query results as JSON, and PATH mode is the standard way to shape relational rows into JSON for downstream application or AI use.
To extract the answer field from the response , the correct command is JSON_VALUE because answer is a single scalar field . Microsoft states that JSON_VALUE is used to extract a scalar value from JSON text.
To extract the embeddings to store in query_cache , the correct command is JSON_QUERY because embeddings are returned as a JSON array , not a scalar. Microsoft states that JSON_QUERY extracts an object or array from JSON text, which is exactly the right behavior for an embeddings payload.
The unused options are not the best fit here:
* OPENJSON is mainly for shredding JSON into rows and columns.
* AI_GENERATE_CHUNKS is for chunking text, not extracting fields from a response payload.
* VECTOR_DISTANCE computes similarity between vectors and is unrelated to JSON extraction.
* FOR XML PATH produces XML, not JSON.
NEW QUESTION # 63
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: A
NEW QUESTION # 64
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