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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, optimize, and deploy database solutions (35โ40%) | 35-40% | - Implement data platform resources
|
| Topic 2: Implement AI capabilities in database solutions (25โ30%) | 25-30% | - Implement AI features
|
| Topic 3: Design and develop database solutions (35โ40%) | 35-40% | - Design and implement relational database schemas
|
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NEW QUESTION # 35
You have a SQL database in Microsoft Fabric that contains a table named dbo.Orders, dbo.Orders has a clustered index, contains three years of data, and is partitioned by a column named OrderDate by month.
You need to remove all the rows for the oldest month. The solution must minimize the impact on other queries that access the data in dbo.orders.
Solution: Run the following Transact-SQL statement.
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(nonth, -36, SYSUTCDATETIME());
Does this meet the goal?
Answer: A
Explanation:
This does not meet the goal. A row-by-row DELETE against the oldest month is not the lowest-impact way to purge data from a monthly partitioned table. Microsoft's partitioning guidance specifically says partitioning lets you perform maintenance and retention operations more efficiently by targeting just the relevant partition, including the ability to truncate data in a single partition .
The proposed statement:
DELETE FROM dbo.Orders
WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());
would log row deletions and can hold locks longer, creating more overhead for other queries than a partition- level maintenance operation. Since the table is already partitioned by month , the expected low-impact approach is to operate on the oldest partition directly, not issue a broad delete predicate over rows. Microsoft explicitly highlights partition-targeted truncation as a faster, more efficient retention operation than working against the whole table or rowset.
NEW QUESTION # 36
You have an Azure SQL database named SalesDB that contains a table named dbo. Articles, dbo.Articles contains two million articles with embeddmgs. The articles are updated frequently throughout the day.
You query the embeddings by using VECTOR_SEARQi
Users report that semantic search results do NOT reflect the updates until the following day.
Vou need to ensure that the embeddings are updated whenever the articles change. The solution must minimize CPU usage on SalesDB Which embedding maintenance method should you implement?
Answer: C
Explanation:
The correct answer is B because the problem is not the vector search operator itself. The problem is that embeddings are becoming stale when article content changes . Microsoft documents that change data capture (CDC) tracks insert, update, and delete operations on source tables, which makes it the right mechanism to identify only the rows that changed.
This also best satisfies the requirement to minimize CPU usage on SalesDB . With CDC, the database only records the row changes, and the embedding regeneration work can be moved to an external process such as an Azure Functions app. That avoids running embedding generation inline inside the database for every update and avoids repeatedly recalculating embeddings for unchanged rows. In contrast, an hourly full-table regeneration would be extremely wasteful on a table with two million frequently updated articles, and a trigger that calls embedding generation per row would push expensive AI work into the transactional path of the database.
Option A is incorrect because changing from VECTOR_SEARCH to VECTOR_DISTANCE does not regenerate embeddings; it only changes the retrieval method. Microsoft states that VECTOR_SEARCH is the ANN search function, while VECTOR_DISTANCE performs exact distance calculation, so neither option addresses stale embedding data.
So the right design is:
* use CDC to detect only changed articles,
* process those changes outside the database,
* regenerate embeddings only for changed rows,
* write back the refreshed embeddings for current semantic search results.
NEW QUESTION # 37
You have an Azure SQL database that stores order data. A reporting query aggregates monthly revenue per customer runs frequently.
You need to reduce how long it takes to retrieve the calculated values. The solution must NOT alter any underlying table structure. What should you do?
Answer: B
Explanation:
To speed up repeated aggregate retrieval without changing base-table structure, the right pattern is an indexed view . Microsoft requires that an indexed view be created with WITH SCHEMABINDING , and if the view uses GROUP BY , it must also include COUNT_BIG(*) . After that, the first index on the view must be a unique clustered index .
The other options fail Microsoft's indexed-view rules:
* A is invalid because ORDER BY is not allowed in the indexed-view definition.
* B is invalid because indexed views require WITH SCHEMABINDING , and the first index cannot just be a nonclustered index.
* C is incomplete because a grouped indexed view must include COUNT_BIG(*) .
NEW QUESTION # 38
You are developing an Azure SQL database solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
You need to ensure that GitHub Copilot Chat can call the hosted GitHub MCP Server tools by using OAuth.
The MCP server configuration must be scoped to the repository.
What should you do in Visual Studio Code?
Answer: C
NEW QUESTION # 39
Drag and Drop Question
You have an Azure SQL database that supports an OLTP application.
You need to write Transact-SQL code that returns blocking chain details. The output must return only sessions that are blocked or are blocking other sessions.
How should you complete the 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:
NEW QUESTION # 40
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A steadily rising competition has been noted in the tech field. Countless candidates around the globe aspire to be Developing AI-Enabled Database Solutions in this field. Once you become Microsoft certified, a whole new scope opens up to you and you are immediately hired by reputed firms. Even though the Developing AI-Enabled Database Solutions certification boosts your career options, you have to pass the DP-800 Exam.
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