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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement AI capabilities in database solutions | 25-30% | - Use AI-assisted development tools
|
| Topic 2: Design and develop database solutions | 35-40% | - Design database solutions
|
| Topic 3: Secure, optimize, and deploy database solutions | 35-40% | - Optimize performance and reliability
|
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NEW QUESTION # 83
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: A
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 # 84
Case Study 1 - Contoso
Existing Environment
Azure Environment
Contoso has an Azure subscription in North Europe that contains the corporate infrastructure.
The current infrastructure contains a Microsoft SQL Server 2017 database. The database contains the following tables.
The FeedbackJsoncolumn has a full-text index and stores JSON documents in the following format.
The support staff at Contoso never has the UNMASKpermission.
Problem Statements
Contoso is deploying a new Azure SQL database that will become the authoritative data store for the following:
* AI workloads
* Vector search
* Modernized API access
* Retrieval Augmented Generation (RAG) pipelines
Sometimes the ingestion pipeline fails due to malformed JSON and duplicate payloads.
The engineers at Contoso report that the following dashboard query runs slowly.
You review the execution plan and discover that the plan shows a clustered index scan.
VehicleIncidentReportsoften contains details about the weather, traffic conditions, and location. Analysts report that it is difficult to find similar incidents based on these details.
Requirements
Planned Changes
Contoso wants to modernize Fleet Intelligence Platform to support AI-powered semantic search over incident reports.
Security Requirements
Contoso identifies the following security requirements:
* Restrict the support staff from viewing Personally Identifiable Information (PII) data, which is full email addresses and phone numbers.
* Enforce row-level filtering so that analysts see only incidents for the fleets to which they are assigned. The analysts can be assigned to multiple fleets.
Database Performance and Requirements
Contoso identifies the following telemetry requirements:
* Telemetry data must be stored in a partitioned table.
* Telemetry data must provide predictable performance for ingestion and retention operations.
* latitude, longitude, and accuracyJSON properties must be filtered by using an index seek.
Contoso identifies the following maintenance data requirements:
* Ensure that any changes to a row in the MaintenanceEventstable updates the corresponding value in the LastModifiedUtccolumn to the time of the change.
* Avoid recursive updates.
AI Search, Embeddings, and Vector Indexing
Contoso plans to implement semantic search over incident data to meet the following requirements:
* Embeddings must be stored in dedicated Azure SQL Database tables.
* Embeddings must be generated from rich natural language fields.
* Chunking must preserve semantic coherence.
* Hybrid search must combine the following:
- Vector similarity
- Keyword filtering or boosting
Development Requirements
The development team at Contoso will use Microsoft Visual Studio Code and GitHub Copilot and will retrieve live metadata from the databases.
Contoso identifies the following requirements for querying data in the FeedbackJsoncolumn of the CustomerFeedbacktable:
* Extract the customer feedback text from the JSON document.
* Filter rows where the JSON text contains a keyword.
* Calculate a fuzzy similarity score between the feedback text and a known issue description.
* Order the results by similarity score, with the highest score first.
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: A,C
Explanation:
Scenario: Sometimes the ingestion pipeline fails due to malformed JSON and duplicate payloads.
Adding a CHECK constraint with ISJSON and creating a unique index on a computed hash of the payload are effective measures in Azure SQL Database to handle malformed JSON and duplicate payloads.
[E]
JSON Validation with a CHECK Constraint
You can use a CHECK constraint in conjunction with the built-in ISJSON function to ensure that only valid JSON text is stored in a VARCHAR or NVARCHAR column. The constraint automatically rejects any insert or update operation that contains malformed JSON data, preventing pipeline failures due to invalid formatting at the database level.
[D]
Deduplication with a Unique Index on a Hashed Payload
To prevent duplicate payloads, you can create a unique index on a computed column that stores a hash of the entire JSON payload or relevant business keys within the JSON.
Reference:
https://www.shaped.ai/blog/10-best-practices-in-data-ingestion
NEW QUESTION # 85
You need to recommend a solution to lesolve the slow dashboard query issue. What should you recommend?
Answer: A
Explanation:
The best recommendation is B because the slow query filters on FleetId and returns LastUpdatedUtc , EngineStatus , and BatteryHealth . A nonclustered index with FleetId as the key column allows the optimizer to perform an index seek instead of a clustered index scan, and including the other selected columns makes the index covering , which reduces extra lookups and I/O. Microsoft's SQL Server indexing guidance states that a nonclustered index with included columns can significantly improve performance when all query columns are available in the index, because the optimizer can satisfy the query directly from the index.
The query is:
SELECT VehicleId, LastUpdatedUtc, EngineStatus, BatteryHealth
FROM dbo.VehicleHealthSummary
WHERE FleetId = @FleetId
ORDER BY LastUpdatedUtc DESC;
Among the given choices, FleetId is the most important search argument because it appears in the WHERE predicate. Microsoft's index design guidance recommends putting columns used for searching in the key and using nonkey included columns to cover the rest of the query efficiently.
Why the other options are weaker:
* A is not appropriate because changing the clustered index to LastUpdatedUtc would not target the main filter predicate on FleetId, and a table can have only one clustered index.
* C makes LastUpdatedUtc the key, which is poor for a query whose primary filter is FleetId.
* D is not the right answer here because the query requirement does not specify only recent rows, and filtered indexes are meant for a well-defined subset; this option also uses a time-based expression that is not aligned to the stated query pattern.
Strictly speaking, the most optimal design for both filtering and ordering would usually be a composite key like (FleetId, LastUpdatedUtc), but since that is not one of the available options, B is the correct exam answer.
NEW QUESTION # 86
Vou have a Microsoft Fabric workspace named Workspace1 that contains a SQL database named SalesDB and an API for GraphQL tern named SalesApi.
You have a Microsoft Entra group named SqlUsers.
From Workspace1, you assign permission to SalesApi as shown in the following exhibit.
The connection to SalesDB has the connectivity option configured as shown in the following exhibit.
SqlUsers has the Viewer role for Workspace1.
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:
Explanation:
* The members of SqlUsers can modify the data in SalesDB via SalesApi. # No
* The members of SqlUsers can view the data in SalesDB via SalesApi. # No
* The members of SqlUsers can change the field mappings of SalesApi. # Yes For both viewing and modifying data through SalesApi, the key missing permission is Run Queries and Mutations . Microsoft's Fabric GraphQL documentation states that callers need Execute permissions for the GraphQL API , which correspond to the Run Queries and Mutations option, and with SSO connectivity they also need appropriate permissions on the underlying data source. In the exhibit, SqlUsers has View and Edit GraphQL item selected, but Run Queries and Mutations is not selected, so members cannot query or mutate data through the API.
The third statement is Yes because the group was explicitly granted View and Edit GraphQL item . That permission is the one that allows users to open and modify the GraphQL item itself, including schema-related configuration such as field mappings in the API item. The workspace Viewer role does not by itself grant query execution through the API, but the direct GraphQL item permission shown does allow editing the item.
NEW QUESTION # 87
You have a GitHub Enterprise subscription.
Your team is developing an Azure SQL dataset solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
A mix of GitHub Copilot instructions is configured at different levels, including organization-wide, repository-wide, agent-specific, and personal.
Which instructions will take precedence over the others?
Answer: C
Explanation:
In a GitHub Enterprise environment, personal instructions (user-level) generally have the highest precedence for individual interactions in VS Code.
Order of Precedence
When GitHub Copilot processes instructions, it follows a "specific-to-general" hierarchy. The most specific context (the individual user) typically overrides broader organizational settings.
1. Personal Instructions
Set via .github/copilot-instructions.md in your local home directory or VS Code settings.
Overrides all other layers for your specific session.
2. Agent-Specific / Extension Instructions
Specific instructions provided to a custom agent (like @workspace or a custom Chat participant).
3. Repository-wide Instructions
Stored in the .github/copilot-instructions.md file within the specific repository.
4. Organization-wide Policies
Set by Enterprise/Org admins. These usually act as "guardrails" (e.g., blocking suggestions) rather than stylistic instructions.
Reference:
https://aiddbot.com/vscode-and-github-copilot
NEW QUESTION # 88
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