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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Developing AI-Enabled Database Solutions (DP-800) |
| Exam Number: | DP-800 |
| Passing Score: | 700/1000 (typical Microsoft passing score; subject to confirmation) |
| Available Languages: | English |
| Certificate Validity Period: | 1 year (Microsoft role-based certifications require annual renewal) |
| Exam Format: | Case studies, Multiple choice |
| 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 # 75
You have an Azure SQL database that supports an AI-driven product search API.
You need to identify the top CPU-consuming queries from the last two hours by using Query Store data. The solution must aggregate CPU consumption across executions and return only the top 15 query hashes.
How should you complete the Transact-SQL code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified Answer : =
* CPU aggregation expression # rs.avg_cpu_time
* Runtime interval source # sys.query_store_runtime_stats_interval
* Last two hours filter # DATEADD(HOUR, -2, GETUTCDATE())
Comprehensive and Detailed Explanation with all Developing AI-Enabled Database Solutions documents : = The first correct selection is rs.avg_cpu_time . Query Store stores CPU statistics per aggregation interval, and Microsoft documents avg_cpu_time as the average CPU time per execution, in microseconds . To calculate total CPU consumption across all executions, multiply count_executions by avg_cpu_time , then divide by
1000.0 to convert microseconds to milliseconds:
SUM(count_executions * rs.avg_cpu_time / 1000.0)
This is the exact pattern Microsoft uses in its documented query for identifying the top 15 CPU-consuming queries by query hash .
The second selection is sys.query_store_runtime_stats_interval because sys.query_store_runtime_stats.
runtime_stats_interval_id is a foreign key to this view. The interval view provides start_time and end_time , allowing Query Store data to be limited to the required time window.
The third selection is DATEADD(HOUR, -2, GETUTCDATE()) . Microsoft's own Azure SQL performance- monitoring example for the last two hours uses exactly:
rsi.start_time > = DATEADD(HOUR, -2, GETUTCDATE())
and then ranks by total CPU descending to return the top 15 query hashes.
Final drag-and-drop selections:
* First target: rs.avg_cpu_time
* Second target: sys.query_store_runtime_stats_interval
* Third target: DATEADD(HOUR, -2, GETUTCDATE())
NEW QUESTION # 76
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 # 77
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.
Hotspot Question
You are creating a table that will store customer profiles.
You have the following Transact-SQL code.
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 # 78
You have a SQL database in Microsoft Fabric that contains a column named Payload. Payload stores customer data in JSON documents that have the following format.
Data analysis shows that some customers have subaddressing in their email address, for example, user1+promo@contoso.com.
You need to return a normalized email value that removes the subaddressing, for example, user1
+promo@contoso.com must be normalized to user1@contoso.com.
Which Transact-SQL expression should you use?
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