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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Exam Price: | $165 USD |
| Certificate Validity Period: | 1 year |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 |
| Exam Format: | Multiple choice, Build list, Drag and drop, Case studies, Multiple select |
| Available Languages: | Indonesian (Indonesia), Portuguese (Brazil), Japanese, Chinese (Simplified), Spanish, Italian, English, German, Chinese (Traditional), Arabic (Saudi Arabia), Korean, French |
| Exam Duration: | 100 minutes |
| Related Certifications: | Microsoft Certified: SQL AI Developer Associate |
| 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 # 79
Hotspot Question
Your company has an ecommerce catalog in a Microsoft SQL Server 2025 database named SalesDB. SalesDB contains a table named products. products contains the following columns:
- product_id (int)
- product_name (nvarchar(200))
- description (nvarchar(max))
- category (nvarchar(50))
- brand (nvarchar(50))
- price (decimal)
- sku (nvarchar(40))
The description fields are updated daily by a content pipeline, and price can change multiple times per day.
You want customers to be able to submit natural language queries and apply structured filters for brand and price.
You plan to store embeddings in a new VECTOR(1536) column and use VECTOR_SEARCH(...
METRIC='cosine' ...).
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 # 80
You need to recommend a solution to lesolve the slow dashboard query issue. What should you recommend?
Answer: D
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 # 81
You need to design a generative Al solution that uses a Microsoft SOL Server 2025 database named DB1 as a data source. The solution must generate responses that meet the following requirements:
* Ait ' grounded In the latest transactional and reference data stored in D61
* Do NOT require retraining or fine-tuning the language model when the data changes
* Can include citations or references to the source data used in the response Which scenario is the best use case for implementing a Retrieval Augmented Generation (RAG) pattern?
More than one answer choice may achieve the goal. Select the BEST answer
Answer: B
Explanation:
The best use case for RAG is answering user questions based on company-specific knowledge . Microsoft defines RAG as a pattern that augments a language model with a retrieval system that provides grounding data at inference time, which is exactly what you need when responses must be based on the latest transactional and reference data , must avoid retraining/fine-tuning , and should be able to include citations or references to source data.
The other options do not fit as well:
* summarizing free-form user input does not inherently require retrieval from DB1,
* training a custom model contradicts the requirement to avoid retraining/fine-tuning,
* generating marketing slogans is a creative generation task, not a grounding-and-citation scenario. RAG is specifically strong when answers must come from your organization's own changing knowledge.
NEW QUESTION # 82
You have an Azure SQL database that contains a table named Sales.Orders. Sales.Orders contains the following columns.
Reporting queries frequently repeat logic to calculate the number of days since an order was placed.
You need to create a scalar user-defined function (UDF) that returns the number of days between an input value of @OrderDate and the current date and time.
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. 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:
* Function return type # RETURNS INT
* Calculation # DATEDIFF(day, @OrderDate, GETDATE())
Comprehensive and Detailed Explanation with all Developing AI-Enabled Database Solutions documents : = The first correct selection is RETURNS INT because the requirement is to create a scalar UDF that returns a single integer representing the number of days since the order date. Microsoft documents that scalar user- defined functions return a single scalar value, and DATEDIFF returns an int value.
The second correct selection is:
DATEDIFF(day, @OrderDate, GETDATE())
Microsoft defines DATEDIFF(datepart, startdate, enddate) as returning the number of specified datepart boundaries crossed between two dates. Therefore, placing @OrderDate as the start date and GETDATE() as the end date returns the number of elapsed day boundaries from the order date to the current date and time.
GETDATE() is valid inside a Transact-SQL UDF. Microsoft explicitly lists GETDATE among the nondeterministic built-in functions that can be used in T-SQL user-defined functions . Its nondeterministic nature means the result changes over time, but it does not prevent creation of this scalar UDF.
The completed code is:
CREATE FUNCTION dbo.ufn_DaysSinceOrder
(
@OrderDate datetime2(0)
)
RETURNS INT
BEGIN
DECLARE @Days int;
SELECT @Days =
DATEDIFF(day, @OrderDate, GETDATE());
RETURN @Days;
END;
GO
So the drag-and-drop answers are:
* First target: RETURNS INT
* Second target: DATEDIFF(day, @OrderDate, GETDATE())
NEW QUESTION # 83
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:
Explanation:
* Unit tests run automatically whenever changes are pushed to main. # Yes
* Schema validation occurs during the Build step. # Yes
* Schema validation occurs during the Deploy step. # No
The first statement is Yes . The workflow is configured to trigger on both push to main and pull_request targeting main. The unit-tests job has this condition:
if: github.ref == ' refs/heads/main '
On a push to main , GitHub sets github.ref to refs/heads/main, so the condition is true and the unit-tests job runs. GitHub's workflow syntax documentation confirms that push.branches: [main] triggers on pushes to main, and the github.ref value for branch pushes is the fully qualified ref such as refs/heads/main.
The second statement is Yes . The Build step runs:
dotnet build db1.sqlproj --configuration Release
For an SDK-style SQL database project, the build process produces a .dacpac and validates the database project model as part of compilation/build. Microsoft's SQL database project documentation describes SDK- style SQL projects as the project format used for SQL Database Projects, and Microsoft's command-line build documentation is specifically about building a .dacpac from that SQL project. That means schema-level project validation happens during build.
The third statement is No . The Deploy step uses:
SqlPackage /Action:Publish ...
Microsoft documents that SqlPackage Publish incrementally updates the target database schema to match the source .dacpac. That is a deployment operation, not the primary schema-validation stage of the SQL project source itself. In this workflow, the schema is validated when the SQL project is built into the .dacpac; the deploy step applies that built artifact to the target database.
NEW QUESTION # 84
......
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