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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, optimize, and deploy database solutions | 35-40% | - Optimize performance and reliability
|
| Topic 2: Design and develop database solutions | 35-40% | - Design database solutions
|
| Topic 3: Implement AI capabilities in database solutions | 25-30% | - Integrate AI models and services
|
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NEW QUESTION # 86
You have an Azure SQL database that supports a customer-facing API. The API calls a stored procedure named dbo.GetCustomerOrders thousands of times per hour.
After a deployment that updated indexes and statistics, users report that the API endpoint backed by dbo.
Getcustomerorders is slower. In Query Store, the same query now has two persisted execution plans. During the last hour, the newer plan had a significantly higher average duration and CPU time than the older plan.
You need to restore the previous performance quickly, without changing the API code.
Which Transact-SQL command should you run?
Answer: D
Explanation:
The scenario says Query Store already shows two persisted execution plans for the same query, and the older plan performed much better than the newer one during the last hour. Microsoft documents that sp_query_store_force_plan is used to force a particular plan for a particular query in Query Store .
That makes it the fastest way to restore the previously good plan without changing application code , which is exactly what the question requires.
Why the other options are not the best fit:
* sp_query_store_set_hints is for adding or updating Query Store hints to influence compilation behavior, but when you already know the exact older good plan, Microsoft points to plan forcing as the direct remedy.
* DBCC FREEPROCCACHE clears cached plans broadly and is disruptive; it does not guarantee a return to the known good plan.
* ALTER DATABASE is too general and does not directly restore the prior execution plan.
So the right Transact-SQL command is:
EXEC sp_query_store_force_plan
using the relevant @query_id and @plan_id from Query Store for the older, better-performing plan.
Microsoft also notes that when a plan is forced, SQL Server tries to use that plan whenever it encounters the query again.
NEW QUESTION # 87
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
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 # 88
You have a database named DB1. The schema is stored in a GitHub repository as an SDK style SQL database project.
You use a feature branch workflow to deploy changes to DB1
You need to update the local feature branch with the latest changes to main, and then create a pull request to merge the feature branch into main for review.
How should you complete the GitHub CLI script? To answer, drag the appropriate values to the correct targets. Each value may be used once, more 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 sequence is:
* git fetch origin
* git merge origin/main
* gh pr create
This is the right workflow because the script starts on the local feature branch:
git checkout feature/db1-add-staticdata
To update that local feature branch with the latest changes from main, you first fetch the latest remote refs with git fetch origin , then merge the updated remote main branch into the current feature branch with git merge origin/main . After the feature branch is up to date, the correct GitHub CLI command to open the pull request is gh pr create . GitHub's CLI documentation shows that gh pr create is the command used to create a pull request, and supports flags such as --title, --body, --head, --base, --repo, and --web, which match the script shown in the question.
The other commands are not the best fit here:
* git checkout main would move you off the feature branch, which is not what you want before merging main into the feature branch.
* git pull origin main could update from remote main, but the script pattern here clearly separates fetching and then merging.
* gh pr merge merges an existing pull request, not create one.
* gh pr ready marks a draft PR as ready for review, but does not create the PR.
NEW QUESTION # 89
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 need to create a solution that meets the development requirements for retrieving the patient transaction data. The solution must ensure that database developers use the resulting data to join to other tables.
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:
NEW QUESTION # 90
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 # 91
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