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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Developing AI-Enabled Database Solutions (DP-800) |
| Exam Number: | DP-800 |
| Available Languages: | English |
| Certificate Validity Period: | 1 year (Microsoft role-based certifications require annual renewal) |
| Exam Format: | Case studies, Multiple choice |
| Passing Score: | 700/1000 (typical Microsoft passing score; subject to confirmation) |
| Recommended Training: | Microsoft Learn - Azure Data & AI Learning Paths |
| Exam Registration: | Microsoft Certification Dashboard |
| Sample Questions: | Microsoft DP-800 Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | No formal prerequisites required, but familiarity with Azure data services and database concepts is recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/ |
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NEW QUESTION # 47
You have an Azure SQL database named ToDo that contains a table named dbo.ToDo.
Your company plans to develop an Azure Functions app to run whenever the rows in dbo.ToDo change. The app will process INSERT, UPDATE, and DELETE events by using the Azure SQL trigger binding.
You need to configure ToDo to support the planned app.
What should you do?
Answer: C
Explanation:
To use the Azure SQL trigger for Azure Functions, your database table must have Change Tracking enabled. This is the underlying mechanism the trigger uses to monitor row-level modifications.
Required Table Configuration
To facilitate the app, you must follow these three steps:
1. Enable Change Tracking on the Database
Before the table can be tracked, the feature must be turned on at the database level.
2. Enable Change Tracking on the Table
The specific table the Function monitors must have tracking enabled.
3. Define a Primary Key
The Azure SQL trigger requires the table to have a Primary Key.
The trigger uses the Primary Key to identify which specific rows were changed.
If your table lacks a Primary Key, the Function will fail to start.
Reference:
https://demiliani.com/2025/05/08/azure-function-sql-trigger-how-to-use-it-and-why-it-can-be- useful-in-your-business-central-projects/
NEW QUESTION # 48
Hotspot Question
You have a database named db1. The schema is stored in a Git repository as an SDK-style SQL database project. The repository contains the following GitHub Action workflow.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 49
You have an Azure SQL database That contains database-level Data Definition Language (DDL) triggers, including a trigger named ddl_Audit.
You need to prevent ddl_Audit from firing during the next deployment. The trigger object must remain in place.
Which Transact-SQL statement should you use?
Answer: A
Explanation:
The requirement is very specific: prevent ddl_Audit from firing during the next deployment , but leave the trigger object in place . Microsoft documents DISABLE TRIGGER as the statement used to disable a trigger without dropping it. That is exactly the right operation for a temporary suspension of a DDL trigger.
For a database-scoped DDL trigger, the syntax is on the database scope, for example DISABLE TRIGGER ddl_Audit ON DATABASE;.
The other options do not meet the requirement as directly:
* ALTER TRIGGER changes the trigger definition, not simply disables execution.
* ALTER DATABASE is not the direct statement for disabling a specific DDL trigger.
* ALTER SERVER AUDIT SPECIFICATION and ALTER DATABASE AUDIT
SPECIFICATION are audit-feature statements, not trigger-control statements.
So the correct Transact-SQL statement is DISABLE TRIGGER .
NEW QUESTION # 50
Vou have an Azure SQL database named SalesDB that contains a table named dbo. Articles, dbo.Articles contains two million articles with embeddmgs. The articles are updated frequently throughout the day.
You query the embeddings by using VECTOR_SEARQi
Users report that semantic search results do NOT reflect the updates until the following day.
Vou need to ensure that the embeddings are updated whenever the articles change. The solution must minimize CPU usage on SalesDB Which embedding maintenance method should you implement?
Answer: C
Explanation:
The correct answer is B because the problem is not the vector search operator itself. The problem is that embeddings are becoming stale when article content changes . Microsoft documents that change data capture (CDC) tracks insert, update, and delete operations on source tables, which makes it the right mechanism to identify only the rows that changed.
This also best satisfies the requirement to minimize CPU usage on SalesDB . With CDC, the database only records the row changes, and the embedding regeneration work can be moved to an external process such as an Azure Functions app. That avoids running embedding generation inline inside the database for every update and avoids repeatedly recalculating embeddings for unchanged rows. In contrast, an hourly full-table regeneration would be extremely wasteful on a table with two million frequently updated articles, and a trigger that calls embedding generation per row would push expensive AI work into the transactional path of the database.
Option A is incorrect because changing from VECTOR_SEARCH to VECTOR_DISTANCE does not regenerate embeddings; it only changes the retrieval method. Microsoft states that VECTOR_SEARCH is the ANN search function, while VECTOR_DISTANCE performs exact distance calculation, so neither option addresses stale embedding data.
So the right design is:
* use CDC to detect only changed articles,
* process those changes outside the database,
* regenerate embeddings only for changed rows,
* write back the refreshed embeddings for current semantic search results.
NEW QUESTION # 51
You have an Azure SQL database that contains a table named Tickets_Embeddings.
Tickets_Embeddings contains a VECTOR(1536) column.
Embeddings are generated by using text-embedding-ada-002 and the /openai/v1/embeddings endpoint.
After a review of the current environment, the following changes are requested:
- The AI architect has recommended switching to text-embedding-3-small.
- The security team requires authentication by using Microsoft Entra
managed identities only. Storing API keys in an application is
prohibited.
Which two actions should you include in the solution? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
Explanation:
To migrate your Azure SQL database to use the text-embedding-3-small model while implementing Microsoft Entra managed identity authentication, you should take the following actions:
[B]
Regenerate all the embeddings: Even though text-embedding-ada-002 and the default configuration of text-embedding-3-small both use 1,536 dimensions, the underlying vector representations are mathematically incompatible. Comparing an "ada" vector to a "v3-small" vector using cosine similarity will yield incorrect results. You must re-embed your existing data using the new model to maintain search accuracy.
[C]
Change the endpoint: To switch models, you must update your application code or database configuration (such as an AI_GENERATE_EMBEDDINGS function call or a stored procedure) to point to the new Azure OpenAI deployment endpoint for text-embedding-3-small.
Why these actions are necessary:
Incompatibility: Vectors generated by different models exist in different latent spaces. While you do not need to Alter the database tables (since the VECTOR(1536) column type remains identical for both models), the actual data inside those columns must be replaced.
Managed Identity: To meet the requirement of using Microsoft Entra managed identities and prohibiting API keys, you must configure your application or the Azure SQL DB to authenticate with Azure OpenAI using a managed identity. This involves granting the identity the Cognitive Services OpenAI User role and updating your connection strings/calls to exclude the api-key header.
Reference:
https://microsoftlearning.github.io/mslearn-postgresql/Instructions/Labs/13-generate-vector- embeddings-azure-openai.html
NEW QUESTION # 52
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DP-800 Valid Exam Testking: https://www.validvce.com/DP-800-exam-collection.html