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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Passing Score: | 700 |
| Real Exam Qty: | 40-60 |
| Exam Price: | $165 USD |
| Related Certifications: | Microsoft Certified: SQL AI Developer Associate |
| Certificate Validity Period: | 1 year |
| Exam Format: | Multiple choice, Multiple select, Drag and drop, Case studies, Build list |
| Available Languages: | Japanese, German, Chinese (Simplified), French, Italian, Chinese (Traditional), Indonesian (Indonesia), English, Arabic (Saudi Arabia), Portuguese (Brazil), Korean, Spanish |
| Exam Duration: | 100 minutes |
| 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 # 56
You have an Azure SQL database that contains the following tables and columns.
Embeddings in the NotesEnbeddings and DescriptionEabeddings tables have been generated from values in the Description and notes columns of the Articles table by using different chunk sizes.
You need to perform approximate nearest neighbor (ANN) queries across both embedding tables. The solution must minimize the impact of using different chunk sizes.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The correct function is VECTOR_SEARCH because the requirement is to perform approximate nearest neighbor (ANN) queries. Microsoft's SQL documentation states that VECTOR_SEARCH is the function used for vector similarity search, and that an ANN index is used only with VECTOR_SEARCH when a compatible vector index exists on the target column. By contrast, VECTOR_DISTANCE calculates an exact distance and does not use a vector index for ANN retrieval.
The correct distance metric is cosine distance. Microsoft documents that VECTOR_SEARCH supports cosine, dot, and euclidean metrics, and Microsoft guidance specifically notes that cosine similarity is commonly used for text embeddings. It also states that retrieval of the most similar texts to a given text typically functions better with cosine similarity, and that Azure OpenAI embeddings rely on cosine similarity to compute similarity between a query and documents. Since both NotesEmbeddings and DescriptionEmbeddings are text-derived embeddings and the goal is to minimize the impact of different chunk sizes, cosine is the best choice because it compares direction/angle rather than being as sensitive to vector magnitude as Euclidean distance.
NEW QUESTION # 57
You have a Microsoft SQL Server 2025 instance that has a managed identity enabled.
You have a database that contains a table named dbo.ManualChunks. dbo.ManualChunks contains product manuals.
A retrieval query already returns the top five matching chunks as nvarchar(max) text.
You need to call an Azure OpenAI REST endpoint for chat completions. The solution must provide the highest level of security.
You write the following Transact-SG1 code.
What should you insert at line 02?
Answer: C
Explanation:
The correct answer is Option B because the requirement is to call an Azure OpenAI REST endpoint from SQL Server 2025 while providing the highest level of security , and the instance already has a managed identity enabled . For Microsoft's SQL AI features, the preferred secure pattern is to use a database scoped credential with IDENTITY = ' Managed Identity ' instead of storing an API key. Microsoft documents that SQL Server 2025 supports managed identity for external AI endpoints, and for Azure OpenAI the credential secret uses the Cognitive Services resource identifier: { " resourceid " : " https://cognitiveservices.azure.
com " } .
So line 02 should be:
WITH IDENTITY = ' Managed Identity ' ,
SECRET = ' { " resourceid " : " https://cognitiveservices.azure.com " } ' ; Why the other options are incorrect:
* A and D use HTTP header or query-string credentials with an API key , which is less secure than managed identity because a secret key must be stored and rotated manually. Microsoft recommends managed identity where supported to avoid embedded secrets.
* C mixes Managed Identity with an api-key secret, which is not the correct pattern for Azure OpenAI managed-identity authentication.
* E uses an invalid identity value for this scenario. The accepted credential identities for external REST endpoint calls include HTTPEndpointHeaders , HTTPEndpointQueryString , Managed Identity , and Shared Access Signature .
Because the endpoint is Azure OpenAI and the question explicitly asks for the highest security , managed identity with the Cognitive Services resource ID is the Microsoft-aligned answer.
NEW QUESTION # 58
You have a database named DB1. The schema is stored in a Git repository as an SDK-style SQL database project.
You have a GitHub Actions workflow that already runs dotnet build and produces a database artifact.
You need to add a deployment step that publishes the .dacpac file to an Azure SQL database by using the secrets stored in GitHub repository secrets.
What should you include in the workflow?
Answer: A
Explanation:
To deploy your .dacpac to Azure SQL using GitHub Actions, you should use the official azure/sql- action@v2. This action is designed specifically to take the output of your dotnet build and publish it.
Assuming your build step is already working, here is how you structure the deployment job.
GitHub Actions Workflow Snippet
Add this job to your .yml file. It depends on your build job (usually named build) and runs on a runner with the Azure CLI installed (like ubuntu-latest).
- name: Deploy SQL Schema
uses: azure/sql-action@v2
with:
connection-string: ${{ secrets.AZURE_SQL_CONNECTION_STRING }}
path: './bin/Release/netstandard2.1/YourDatabase.dacpac' # Path to your .dacpac action: 'publish' Incorrect:
[Not A]
Use connection-string: ${{ secrets.AZURE_SQL_CONNECTION_STRING }}
[Not B]
Action set to publish, not to extract.
[Not D]
Use azure/sql-action@v2.
Reference:
https://stackoverflow.com/questions/75490960/github-actions-dotnet-publish-specify-a-project- with-a-dot-in-the-name
NEW QUESTION # 59
You have an Azure SQL database.
You deploy Data API builder (DAB) to Azure Container Apps by using the
mcr.microsoft.com/azure-databases/data-api-builder:latest image.
You have the following Container Apps secrets:
- MSSQL_CONNECTION_STRING that maps to the SQL connection string
- DAB_CONFIG_BASE64 that maps to the DAB configuration
You need to initialize the DAB configuration to read the SQL connection string.
Which command should you run?
Answer: D
Explanation:
To initialize the Data API builder (DAB) configuration to read the SQL connection string from your Container Apps secret, use the following dab init command:
dab init --database-type mssql --connection-string "@env('MSSQL_CONNECTION_STRING')" Why this command works
--database-type mssql: Specifies that you are connecting to an Azure SQL or SQL Server database.
@env('MSSQL_CONNECTION_STRING'): This is the built-in DAB function that tells the runtime to substitute the value of the specified environment variable at load time. Since your Container Apps secret is mapped to MSSQL_CONNECTION_STRING, DAB will resolve it automatically when the container starts.
--connection-string: This flag sets the data source connection. By using the @env() syntax here, you ensure the secret remains out of the static configuration file.
Reference:
https://learn.microsoft.com/en-us/azure/data-api-builder/command-line/dab-init
NEW QUESTION # 60
Case Study 2 - Fabrikam
Existing Environment
Azure Environment
Fabrikam has a single Azure subscription in the East US 2 Azure region. The subscription contains an Azure SQL database named DB1. DB1 contains the following tables:
* Patients
* Employees
* Procedures
* Transactions
* UsefulPrompts
* ProcedureDocuments
You store a column master key as a secret in Azure Key Vault.
You have an on-premises application named TransactionProcessing that uses a hard-coded username and password in a connection string to access DB1.
Problem Statements
Users report that after executing a long-running stored procedure named sp_UpdateProcedureForPatient, updates to the underlying data are sometimes inconsistent.
Requirements
Planned Changes
Fabrikam plans to manage all changes to Azure SQL Database objects by using source control in GitHub. Every pull request submitted to production will be validated before it can be merged.
Deployments must use the Release configuration.
Security Requirements
Fabrikam identifies the following security requirements:
* The TransactionProcessing application must use a passwordless connection to DB1.
* The Employees table contains two columns named TaxID and Salary that must be encrypted at rest.
* Auditors must have a tamper-evident history of transactions with cryptographic proof of changes to the employee data.
Database Performance Requirements
Records accessed by using sp_UpdateProcedureForPatient must NOT be changed by other transactions while the stored procedure runs.
AI Search, Embeddings, and Vector Indexing
Fabrikam identifies the following AI-related requirements:
* Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF).
* Users must be able to query the data in DB1 by using prompts in Copilot in Microsoft Fabric.
* The UsefulPrompts table will store prompts that doctors can use to help diagnose patient illness by connecting to an Azure OpenAI endpoint.
Development Requirements
Fabrikam identifies the following development requirements:
* Provide the functionality to retrieve all the transactions of a given patient between two dates, showing a running total.
* Expose a Data API builder (DAB) configuration file to enable Azure services to perform the following operations over a REST API:
- Read data from the procedures table without authentication.
- Read and insert data into the Transactions table once authenticated.
- Execute the sp_UpdateProcedurePatient stored procedure.
* Provide the functionality to retrieve a list of the names of patients who underwent medical procedures during the last 30 days.
* Information for each medical procedure will be stored in a table. The table will be used with a large language model (LLM) for user querying and will have the following structure.
DAB
You create a DAB configuration file that meets the development requirements for DB1 and includes the following entities.
Hotspot Question
You create an SDK-style SQL database project in Microsoft Visual Studio Code named Database.sqlproj and add the project to a GitHub repository.
You need to configure a GitHub Actions workflow to support the planned changes for DB1.
How should you complete the workflow? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 61
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